├── .gitignore ├── Audio ├── 01_rvc_prj_webui_share.ipynb ├── 02_VALL_E_X.ipynb ├── 03_SeamlessM4T.ipynb ├── 04_AudioCraft.ipynb ├── 05_AudioSep.ipynb └── 06_Style_Bert_VITS2.ipynb ├── Language ├── 01_LLaMA2.ipynb ├── 02_Vicuna_7b.ipynb ├── 03_Mistral_7b.ipynb ├── 04_ABEJA_LLM_2_7b.ipynb ├── 05_LLM_jp_13B.ipynb ├── 06_CALM2_7B.ipynb ├── 07_JapaneseStableLM_Gamma_7B.ipynb ├── 08_PLaMo_13B_Instruct.ipynb ├── 09_llama_cpp.ipynb ├── 10_AutoGPTQ.ipynb ├── 11_llama2_QLoRA.ipynb ├── 12_01_TRL_SFT.ipynb ├── 12_02_TRL_merge.ipynb ├── 12_03_TRL_RM.ipynb ├── 12_04_TRL_PPO.ipynb ├── 12_05_TRL_DPO.ipynb ├── 13_StableCode_3b.ipynb ├── 14_CodeLlama.ipynb ├── 15_Swallow_13B_Instruct.ipynb ├── 16_Mixtral_8x7B.ipynb └── 17_SelfExtend.ipynb ├── MultiModal ├── 01_JapaneseInstructBLIP.ipynb ├── 02_LLaVA.ipynb └── 03_JapaneseStable_VLM.ipynb ├── README.md └── Vision ├── 01_stable_diffusion.ipynb ├── 02_waifu_diffusion.ipynb ├── 03_SDXL.ipynb ├── 04_Emi.ipynb ├── 05_MangaDiffusion.ipynb ├── 06_SDXL_Turbo.ipynb ├── 07_StableDiffusion_LoRA.ipynb ├── 08_LCM_LoRA.ipynb ├── 09_ControlNet.ipynb ├── 10_StableVideoDiffusion.ipynb ├── 11_AnimateDiff.ipynb ├── 12_01_StableDiffusion_DreamBooth_Train.ipynb ├── 12_02_StableDiffusion_DreamBooth_Inference.ipynb ├── 13_CartoonSegmentation.ipynb ├── 14_DreamTalk.ipynb └── 15_StableCascade.ipynb /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | share/python-wheels/ 24 | *.egg-info/ 25 | .installed.cfg 26 | *.egg 27 | MANIFEST 28 | 29 | # PyInstaller 30 | # Usually these files are written by a python script from a template 31 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 32 | *.manifest 33 | *.spec 34 | 35 | # Installer logs 36 | pip-log.txt 37 | pip-delete-this-directory.txt 38 | 39 | # Unit test / coverage reports 40 | htmlcov/ 41 | .tox/ 42 | .nox/ 43 | .coverage 44 | .coverage.* 45 | .cache 46 | nosetests.xml 47 | coverage.xml 48 | *.cover 49 | *.py,cover 50 | .hypothesis/ 51 | .pytest_cache/ 52 | cover/ 53 | 54 | # Translations 55 | *.mo 56 | *.pot 57 | 58 | # Django stuff: 59 | *.log 60 | local_settings.py 61 | db.sqlite3 62 | db.sqlite3-journal 63 | 64 | # Flask stuff: 65 | instance/ 66 | .webassets-cache 67 | 68 | # Scrapy stuff: 69 | .scrapy 70 | 71 | # Sphinx documentation 72 | docs/_build/ 73 | 74 | # PyBuilder 75 | .pybuilder/ 76 | target/ 77 | 78 | # Jupyter Notebook 79 | .ipynb_checkpoints 80 | 81 | # IPython 82 | profile_default/ 83 | ipython_config.py 84 | 85 | # pyenv 86 | # For a library or package, you might want to ignore these files since the code is 87 | # intended to run in multiple environments; otherwise, check them in: 88 | # .python-version 89 | 90 | # pipenv 91 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 92 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 93 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 94 | # install all needed dependencies. 95 | #Pipfile.lock 96 | 97 | # poetry 98 | # Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. 99 | # This is especially recommended for binary packages to ensure reproducibility, and is more 100 | # commonly ignored for libraries. 101 | # https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control 102 | #poetry.lock 103 | 104 | # pdm 105 | # Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. 106 | #pdm.lock 107 | # pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it 108 | # in version control. 109 | # https://pdm.fming.dev/#use-with-ide 110 | .pdm.toml 111 | 112 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm 113 | __pypackages__/ 114 | 115 | # Celery stuff 116 | celerybeat-schedule 117 | celerybeat.pid 118 | 119 | # SageMath parsed files 120 | *.sage.py 121 | 122 | # Environments 123 | .env 124 | .venv 125 | env/ 126 | venv/ 127 | ENV/ 128 | env.bak/ 129 | venv.bak/ 130 | 131 | # Spyder project settings 132 | .spyderproject 133 | .spyproject 134 | 135 | # Rope project settings 136 | .ropeproject 137 | 138 | # mkdocs documentation 139 | /site 140 | 141 | # mypy 142 | .mypy_cache/ 143 | .dmypy.json 144 | dmypy.json 145 | 146 | # Pyre type checker 147 | .pyre/ 148 | 149 | # pytype static type analyzer 150 | .pytype/ 151 | 152 | # Cython debug symbols 153 | cython_debug/ 154 | 155 | # PyCharm 156 | # JetBrains specific template is maintained in a separate JetBrains.gitignore that can 157 | # be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore 158 | # and can be added to the global gitignore or merged into this file. For a more nuclear 159 | # option (not recommended) you can uncomment the following to ignore the entire idea folder. 160 | #.idea/ 161 | .python-version 162 | 163 | *.parquet 164 | .env 165 | .DS_Store 166 | 99_* 167 | tmp/ 168 | bak/ 169 | *.zip 170 | 171 | # Ignore CLI configuration files 172 | .terraformrc 173 | terraform.rc 174 | 175 | # Local .terraform directories 176 | **/.terraform/* 177 | 178 | # .tfstate files 179 | *.tfstate 180 | *.tfstate.* 181 | *.tfvars 182 | -------------------------------------------------------------------------------- /Language/04_ABEJA_LLM_2_7b.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "nbformat": 4, 3 | "nbformat_minor": 0, 4 | "metadata": { 5 | "colab": { 6 | "provenance": [], 7 | "machine_shape": "hm", 8 | "authorship_tag": "ABX9TyMHLxNNEH7nf/qtBIo1oUva", 9 | "include_colab_link": true 10 | }, 11 | "kernelspec": { 12 | "name": "python3", 13 | "display_name": "Python 3" 14 | }, 15 | "language_info": { 16 | "name": "python" 17 | }, 18 | "widgets": { 19 | "application/vnd.jupyter.widget-state+json": { 20 | "7e2fa68518be449f80fd97746305eab0": { 21 | "model_module": "@jupyter-widgets/controls", 22 | "model_name": "HBoxModel", 23 | "model_module_version": "1.5.0", 24 | "state": { 25 | "_dom_classes": [], 26 | "_model_module": "@jupyter-widgets/controls", 27 | "_model_module_version": "1.5.0", 28 | "_model_name": "HBoxModel", 29 | "_view_count": null, 30 | "_view_module": "@jupyter-widgets/controls", 31 | "_view_module_version": "1.5.0", 32 | "_view_name": "HBoxView", 33 | "box_style": "", 34 | "children": [ 35 | "IPY_MODEL_9c9a672fc7b6408c8f36eb48be24257f", 36 | "IPY_MODEL_a1ac3cff06d3416db0b8c9dd9edf48f5", 37 | "IPY_MODEL_f1a3e3ef130348d0877668ad50382a78" 38 | ], 39 | "layout": "IPY_MODEL_19de596f8f60498c908b3adf9d34cd41" 40 | } 41 | }, 42 | "9c9a672fc7b6408c8f36eb48be24257f": { 43 | "model_module": "@jupyter-widgets/controls", 44 | "model_name": "HTMLModel", 45 | "model_module_version": "1.5.0", 46 | "state": { 47 | "_dom_classes": [], 48 | "_model_module": "@jupyter-widgets/controls", 49 | "_model_module_version": "1.5.0", 50 | "_model_name": "HTMLModel", 51 | "_view_count": null, 52 | "_view_module": "@jupyter-widgets/controls", 53 | "_view_module_version": "1.5.0", 54 | "_view_name": "HTMLView", 55 | "description": "", 56 | "description_tooltip": null, 57 | "layout": "IPY_MODEL_04d35b3697a44e58a57ead48479a1a73", 58 | "placeholder": "​", 59 | "style": "IPY_MODEL_c14afb7238044f25ac888f750979ab26", 60 | "value": "tokenizer_config.json: 100%" 61 | } 62 | }, 63 | "a1ac3cff06d3416db0b8c9dd9edf48f5": { 64 | "model_module": "@jupyter-widgets/controls", 65 | "model_name": "FloatProgressModel", 66 | "model_module_version": "1.5.0", 67 | "state": { 68 | "_dom_classes": [], 69 | "_model_module": "@jupyter-widgets/controls", 70 | "_model_module_version": "1.5.0", 71 | "_model_name": "FloatProgressModel", 72 | "_view_count": null, 73 | "_view_module": "@jupyter-widgets/controls", 74 | "_view_module_version": "1.5.0", 75 | "_view_name": "ProgressView", 76 | "bar_style": "success", 77 | "description": "", 78 | "description_tooltip": null, 79 | "layout": "IPY_MODEL_3853ef77d1eb43aeb44cdb44b79b79c3", 80 | "max": 168, 81 | "min": 0, 82 | "orientation": "horizontal", 83 | "style": "IPY_MODEL_97f29a72eda4407b880c17da8a4c54e3", 84 | "value": 168 85 | } 86 | }, 87 | "f1a3e3ef130348d0877668ad50382a78": { 88 | "model_module": "@jupyter-widgets/controls", 89 | "model_name": "HTMLModel", 90 | "model_module_version": "1.5.0", 91 | "state": { 92 | "_dom_classes": [], 93 | "_model_module": "@jupyter-widgets/controls", 94 | "_model_module_version": "1.5.0", 95 | "_model_name": "HTMLModel", 96 | "_view_count": null, 97 | "_view_module": "@jupyter-widgets/controls", 98 | "_view_module_version": "1.5.0", 99 | "_view_name": "HTMLView", 100 | "description": "", 101 | "description_tooltip": null, 102 | "layout": "IPY_MODEL_48f2ee42333243978c5f21f68c242631", 103 | "placeholder": "​", 104 | "style": "IPY_MODEL_ef0c0287d1674492a2bd79e38a32f639", 105 | "value": " 168/168 [00:00<00:00, 11.6kB/s]" 106 | } 107 | }, 108 | "19de596f8f60498c908b3adf9d34cd41": { 109 | "model_module": "@jupyter-widgets/base", 110 | "model_name": "LayoutModel", 111 | "model_module_version": "1.2.0", 112 | "state": { 113 | "_model_module": "@jupyter-widgets/base", 114 | "_model_module_version": "1.2.0", 115 | "_model_name": "LayoutModel", 116 | "_view_count": null, 117 | "_view_module": "@jupyter-widgets/base", 118 | "_view_module_version": "1.2.0", 119 | "_view_name": "LayoutView", 120 | "align_content": null, 121 | "align_items": null, 122 | "align_self": null, 123 | "border": null, 124 | "bottom": null, 125 | "display": null, 126 | "flex": null, 127 | "flex_flow": null, 128 | "grid_area": null, 129 | "grid_auto_columns": null, 130 | "grid_auto_flow": null, 131 | "grid_auto_rows": null, 132 | "grid_column": null, 133 | "grid_gap": null, 134 | "grid_row": null, 135 | "grid_template_areas": null, 136 | "grid_template_columns": null, 137 | "grid_template_rows": null, 138 | "height": null, 139 | "justify_content": null, 140 | "justify_items": null, 141 | "left": null, 142 | "margin": null, 143 | "max_height": null, 144 | "max_width": null, 145 | "min_height": null, 146 | "min_width": null, 147 | "object_fit": null, 148 | "object_position": null, 149 | "order": null, 150 | "overflow": null, 151 | "overflow_x": null, 152 | "overflow_y": null, 153 | "padding": null, 154 | "right": null, 155 | "top": null, 156 | "visibility": null, 157 | "width": null 158 | } 159 | }, 160 | "04d35b3697a44e58a57ead48479a1a73": { 161 | "model_module": "@jupyter-widgets/base", 162 | "model_name": "LayoutModel", 163 | "model_module_version": "1.2.0", 164 | "state": { 165 | "_model_module": "@jupyter-widgets/base", 166 | "_model_module_version": "1.2.0", 167 | "_model_name": "LayoutModel", 168 | "_view_count": null, 169 | "_view_module": "@jupyter-widgets/base", 170 | "_view_module_version": "1.2.0", 171 | "_view_name": "LayoutView", 172 | "align_content": null, 173 | "align_items": null, 174 | "align_self": null, 175 | "border": null, 176 | "bottom": null, 177 | "display": null, 178 | "flex": null, 179 | "flex_flow": null, 180 | "grid_area": null, 181 | "grid_auto_columns": null, 182 | "grid_auto_flow": null, 183 | "grid_auto_rows": null, 184 | "grid_column": null, 185 | "grid_gap": null, 186 | "grid_row": null, 187 | "grid_template_areas": null, 188 | "grid_template_columns": null, 189 | "grid_template_rows": null, 190 | "height": null, 191 | "justify_content": null, 192 | "justify_items": null, 193 | "left": null, 194 | "margin": null, 195 | "max_height": null, 196 | "max_width": null, 197 | "min_height": null, 198 | "min_width": null, 199 | "object_fit": null, 200 | "object_position": null, 201 | "order": null, 202 | "overflow": null, 203 | "overflow_x": null, 204 | "overflow_y": null, 205 | "padding": null, 206 | "right": null, 207 | "top": null, 208 | "visibility": null, 209 | "width": null 210 | } 211 | }, 212 | "c14afb7238044f25ac888f750979ab26": { 213 | "model_module": "@jupyter-widgets/controls", 214 | "model_name": "DescriptionStyleModel", 215 | "model_module_version": "1.5.0", 216 | "state": { 217 | "_model_module": "@jupyter-widgets/controls", 218 | "_model_module_version": "1.5.0", 219 | "_model_name": "DescriptionStyleModel", 220 | "_view_count": null, 221 | "_view_module": "@jupyter-widgets/base", 222 | "_view_module_version": "1.2.0", 223 | "_view_name": "StyleView", 224 | "description_width": "" 225 | } 226 | }, 227 | "3853ef77d1eb43aeb44cdb44b79b79c3": { 228 | "model_module": "@jupyter-widgets/base", 229 | "model_name": "LayoutModel", 230 | "model_module_version": "1.2.0", 231 | "state": { 232 | "_model_module": "@jupyter-widgets/base", 233 | "_model_module_version": "1.2.0", 234 | "_model_name": "LayoutModel", 235 | "_view_count": null, 236 | "_view_module": "@jupyter-widgets/base", 237 | "_view_module_version": "1.2.0", 238 | "_view_name": "LayoutView", 239 | "align_content": null, 240 | "align_items": null, 241 | "align_self": null, 242 | "border": null, 243 | "bottom": null, 244 | "display": null, 245 | "flex": null, 246 | "flex_flow": null, 247 | "grid_area": null, 248 | "grid_auto_columns": null, 249 | "grid_auto_flow": null, 250 | "grid_auto_rows": null, 251 | "grid_column": null, 252 | "grid_gap": null, 253 | "grid_row": null, 254 | "grid_template_areas": null, 255 | "grid_template_columns": null, 256 | "grid_template_rows": null, 257 | "height": null, 258 | "justify_content": null, 259 | "justify_items": null, 260 | "left": null, 261 | "margin": null, 262 | "max_height": null, 263 | "max_width": null, 264 | "min_height": null, 265 | "min_width": null, 266 | "object_fit": null, 267 | "object_position": null, 268 | "order": null, 269 | "overflow": null, 270 | "overflow_x": null, 271 | "overflow_y": null, 272 | "padding": null, 273 | "right": null, 274 | "top": null, 275 | "visibility": null, 276 | "width": null 277 | } 278 | }, 279 | "97f29a72eda4407b880c17da8a4c54e3": { 280 | "model_module": "@jupyter-widgets/controls", 281 | "model_name": "ProgressStyleModel", 282 | "model_module_version": "1.5.0", 283 | "state": { 284 | "_model_module": "@jupyter-widgets/controls", 285 | "_model_module_version": "1.5.0", 286 | "_model_name": "ProgressStyleModel", 287 | "_view_count": null, 288 | "_view_module": "@jupyter-widgets/base", 289 | "_view_module_version": "1.2.0", 290 | "_view_name": "StyleView", 291 | "bar_color": null, 292 | "description_width": "" 293 | } 294 | }, 295 | "48f2ee42333243978c5f21f68c242631": { 296 | "model_module": "@jupyter-widgets/base", 297 | "model_name": "LayoutModel", 298 | "model_module_version": "1.2.0", 299 | "state": { 300 | "_model_module": "@jupyter-widgets/base", 301 | "_model_module_version": "1.2.0", 302 | "_model_name": "LayoutModel", 303 | "_view_count": null, 304 | "_view_module": "@jupyter-widgets/base", 305 | "_view_module_version": "1.2.0", 306 | "_view_name": "LayoutView", 307 | "align_content": null, 308 | "align_items": null, 309 | "align_self": null, 310 | "border": null, 311 | "bottom": null, 312 | "display": null, 313 | "flex": null, 314 | "flex_flow": null, 315 | "grid_area": null, 316 | "grid_auto_columns": null, 317 | "grid_auto_flow": null, 318 | "grid_auto_rows": null, 319 | "grid_column": null, 320 | "grid_gap": null, 321 | "grid_row": null, 322 | "grid_template_areas": null, 323 | "grid_template_columns": null, 324 | "grid_template_rows": null, 325 | "height": null, 326 | "justify_content": null, 327 | "justify_items": null, 328 | "left": null, 329 | "margin": null, 330 | "max_height": null, 331 | "max_width": null, 332 | "min_height": null, 333 | "min_width": null, 334 | "object_fit": null, 335 | "object_position": null, 336 | "order": null, 337 | "overflow": null, 338 | "overflow_x": null, 339 | "overflow_y": null, 340 | "padding": null, 341 | "right": null, 342 | "top": null, 343 | "visibility": null, 344 | "width": null 345 | } 346 | }, 347 | "ef0c0287d1674492a2bd79e38a32f639": { 348 | "model_module": "@jupyter-widgets/controls", 349 | "model_name": "DescriptionStyleModel", 350 | "model_module_version": "1.5.0", 351 | "state": { 352 | "_model_module": "@jupyter-widgets/controls", 353 | "_model_module_version": "1.5.0", 354 | "_model_name": "DescriptionStyleModel", 355 | "_view_count": null, 356 | "_view_module": "@jupyter-widgets/base", 357 | "_view_module_version": "1.2.0", 358 | "_view_name": "StyleView", 359 | "description_width": "" 360 | } 361 | }, 362 | "7aabeac5f94d45938c70d85d5f6030e2": { 363 | "model_module": "@jupyter-widgets/controls", 364 | "model_name": "HBoxModel", 365 | "model_module_version": "1.5.0", 366 | "state": { 367 | "_dom_classes": [], 368 | "_model_module": "@jupyter-widgets/controls", 369 | "_model_module_version": "1.5.0", 370 | "_model_name": "HBoxModel", 371 | "_view_count": null, 372 | "_view_module": "@jupyter-widgets/controls", 373 | "_view_module_version": "1.5.0", 374 | "_view_name": "HBoxView", 375 | "box_style": "", 376 | "children": [ 377 | "IPY_MODEL_6cb27ec0214d4fe38cae4d09ea5146ee", 378 | "IPY_MODEL_d5547266057f45a8b9ae0b88d553fc1f", 379 | "IPY_MODEL_be5c4d04beeb43a2b2da1f7aa1fd3c3d" 380 | ], 381 | "layout": "IPY_MODEL_80d12bc12f194e8aaee9273af820d2a7" 382 | } 383 | }, 384 | "6cb27ec0214d4fe38cae4d09ea5146ee": { 385 | "model_module": "@jupyter-widgets/controls", 386 | "model_name": "HTMLModel", 387 | "model_module_version": "1.5.0", 388 | "state": { 389 | "_dom_classes": [], 390 | "_model_module": "@jupyter-widgets/controls", 391 | "_model_module_version": "1.5.0", 392 | "_model_name": "HTMLModel", 393 | "_view_count": null, 394 | "_view_module": "@jupyter-widgets/controls", 395 | "_view_module_version": "1.5.0", 396 | "_view_name": "HTMLView", 397 | "description": "", 398 | "description_tooltip": null, 399 | "layout": "IPY_MODEL_915790952c444556b003d7295d1c5ccb", 400 | "placeholder": "​", 401 | "style": "IPY_MODEL_b26c3ac3150c46c6853f08a40c88e234", 402 | "value": "config.json: 100%" 403 | } 404 | }, 405 | "d5547266057f45a8b9ae0b88d553fc1f": { 406 | "model_module": "@jupyter-widgets/controls", 407 | "model_name": "FloatProgressModel", 408 | "model_module_version": "1.5.0", 409 | "state": { 410 | "_dom_classes": [], 411 | "_model_module": "@jupyter-widgets/controls", 412 | "_model_module_version": "1.5.0", 413 | "_model_name": "FloatProgressModel", 414 | "_view_count": null, 415 | "_view_module": "@jupyter-widgets/controls", 416 | "_view_module_version": "1.5.0", 417 | "_view_name": "ProgressView", 418 | "bar_style": "success", 419 | "description": "", 420 | "description_tooltip": null, 421 | "layout": "IPY_MODEL_4133abb3166e49fa9d1f851d97d15741", 422 | "max": 602, 423 | "min": 0, 424 | "orientation": "horizontal", 425 | "style": "IPY_MODEL_183c7fbb1b464b7fbdc37f1042def7df", 426 | "value": 602 427 | } 428 | }, 429 | "be5c4d04beeb43a2b2da1f7aa1fd3c3d": { 430 | "model_module": "@jupyter-widgets/controls", 431 | "model_name": "HTMLModel", 432 | "model_module_version": "1.5.0", 433 | "state": { 434 | "_dom_classes": [], 435 | "_model_module": "@jupyter-widgets/controls", 436 | "_model_module_version": "1.5.0", 437 | "_model_name": "HTMLModel", 438 | "_view_count": null, 439 | "_view_module": "@jupyter-widgets/controls", 440 | "_view_module_version": "1.5.0", 441 | "_view_name": "HTMLView", 442 | "description": "", 443 | "description_tooltip": null, 444 | "layout": "IPY_MODEL_2f7a0c6355ef48669b8889a0cdc86d30", 445 | "placeholder": "​", 446 | "style": "IPY_MODEL_60198bd7296549bebfa02d030e153098", 447 | "value": " 602/602 [00:00<00:00, 41.3kB/s]" 448 | } 449 | }, 450 | "80d12bc12f194e8aaee9273af820d2a7": { 451 | "model_module": "@jupyter-widgets/base", 452 | "model_name": "LayoutModel", 453 | "model_module_version": "1.2.0", 454 | "state": { 455 | "_model_module": "@jupyter-widgets/base", 456 | "_model_module_version": "1.2.0", 457 | "_model_name": "LayoutModel", 458 | "_view_count": null, 459 | "_view_module": "@jupyter-widgets/base", 460 | "_view_module_version": "1.2.0", 461 | "_view_name": "LayoutView", 462 | "align_content": null, 463 | "align_items": null, 464 | "align_self": null, 465 | "border": null, 466 | "bottom": null, 467 | "display": null, 468 | "flex": null, 469 | "flex_flow": null, 470 | "grid_area": null, 471 | "grid_auto_columns": null, 472 | "grid_auto_flow": null, 473 | "grid_auto_rows": null, 474 | "grid_column": null, 475 | "grid_gap": null, 476 | "grid_row": null, 477 | "grid_template_areas": null, 478 | "grid_template_columns": null, 479 | "grid_template_rows": null, 480 | "height": null, 481 | "justify_content": null, 482 | "justify_items": null, 483 | "left": null, 484 | "margin": null, 485 | "max_height": null, 486 | "max_width": null, 487 | "min_height": null, 488 | "min_width": null, 489 | "object_fit": null, 490 | "object_position": null, 491 | "order": null, 492 | "overflow": null, 493 | "overflow_x": null, 494 | "overflow_y": null, 495 | "padding": null, 496 | "right": null, 497 | "top": null, 498 | "visibility": null, 499 | "width": null 500 | } 501 | }, 502 | "915790952c444556b003d7295d1c5ccb": { 503 | "model_module": "@jupyter-widgets/base", 504 | "model_name": "LayoutModel", 505 | "model_module_version": "1.2.0", 506 | "state": { 507 | "_model_module": "@jupyter-widgets/base", 508 | "_model_module_version": "1.2.0", 509 | "_model_name": "LayoutModel", 510 | "_view_count": null, 511 | "_view_module": "@jupyter-widgets/base", 512 | "_view_module_version": "1.2.0", 513 | "_view_name": "LayoutView", 514 | "align_content": null, 515 | "align_items": null, 516 | "align_self": null, 517 | "border": null, 518 | "bottom": null, 519 | "display": null, 520 | "flex": null, 521 | "flex_flow": null, 522 | "grid_area": null, 523 | "grid_auto_columns": null, 524 | "grid_auto_flow": null, 525 | "grid_auto_rows": null, 526 | "grid_column": null, 527 | "grid_gap": null, 528 | "grid_row": null, 529 | "grid_template_areas": null, 530 | "grid_template_columns": null, 531 | "grid_template_rows": null, 532 | "height": null, 533 | "justify_content": null, 534 | "justify_items": null, 535 | "left": null, 536 | "margin": null, 537 | "max_height": null, 538 | "max_width": null, 539 | "min_height": null, 540 | "min_width": null, 541 | "object_fit": null, 542 | "object_position": null, 543 | "order": null, 544 | "overflow": null, 545 | "overflow_x": null, 546 | "overflow_y": null, 547 | "padding": null, 548 | "right": null, 549 | "top": null, 550 | "visibility": null, 551 | "width": null 552 | } 553 | }, 554 | "b26c3ac3150c46c6853f08a40c88e234": { 555 | "model_module": "@jupyter-widgets/controls", 556 | "model_name": "DescriptionStyleModel", 557 | "model_module_version": "1.5.0", 558 | "state": { 559 | "_model_module": "@jupyter-widgets/controls", 560 | "_model_module_version": "1.5.0", 561 | "_model_name": "DescriptionStyleModel", 562 | "_view_count": null, 563 | "_view_module": "@jupyter-widgets/base", 564 | "_view_module_version": "1.2.0", 565 | "_view_name": "StyleView", 566 | "description_width": "" 567 | } 568 | }, 569 | "4133abb3166e49fa9d1f851d97d15741": { 570 | "model_module": "@jupyter-widgets/base", 571 | "model_name": "LayoutModel", 572 | "model_module_version": "1.2.0", 573 | "state": { 574 | "_model_module": "@jupyter-widgets/base", 575 | "_model_module_version": "1.2.0", 576 | "_model_name": "LayoutModel", 577 | "_view_count": null, 578 | "_view_module": "@jupyter-widgets/base", 579 | "_view_module_version": "1.2.0", 580 | "_view_name": "LayoutView", 581 | "align_content": null, 582 | "align_items": null, 583 | "align_self": null, 584 | "border": null, 585 | "bottom": null, 586 | "display": null, 587 | "flex": null, 588 | "flex_flow": null, 589 | "grid_area": null, 590 | "grid_auto_columns": null, 591 | "grid_auto_flow": null, 592 | "grid_auto_rows": null, 593 | "grid_column": null, 594 | "grid_gap": null, 595 | "grid_row": null, 596 | "grid_template_areas": null, 597 | "grid_template_columns": null, 598 | "grid_template_rows": null, 599 | "height": null, 600 | "justify_content": null, 601 | "justify_items": null, 602 | "left": null, 603 | "margin": null, 604 | "max_height": null, 605 | "max_width": null, 606 | "min_height": null, 607 | "min_width": null, 608 | "object_fit": null, 609 | "object_position": null, 610 | "order": null, 611 | "overflow": null, 612 | "overflow_x": null, 613 | "overflow_y": null, 614 | "padding": null, 615 | "right": null, 616 | "top": null, 617 | "visibility": null, 618 | "width": null 619 | } 620 | }, 621 | "183c7fbb1b464b7fbdc37f1042def7df": { 622 | "model_module": "@jupyter-widgets/controls", 623 | "model_name": "ProgressStyleModel", 624 | "model_module_version": "1.5.0", 625 | "state": { 626 | "_model_module": "@jupyter-widgets/controls", 627 | "_model_module_version": "1.5.0", 628 | "_model_name": "ProgressStyleModel", 629 | "_view_count": null, 630 | "_view_module": "@jupyter-widgets/base", 631 | "_view_module_version": "1.2.0", 632 | "_view_name": "StyleView", 633 | "bar_color": null, 634 | "description_width": "" 635 | } 636 | }, 637 | "2f7a0c6355ef48669b8889a0cdc86d30": { 638 | "model_module": "@jupyter-widgets/base", 639 | "model_name": "LayoutModel", 640 | "model_module_version": "1.2.0", 641 | "state": { 642 | "_model_module": "@jupyter-widgets/base", 643 | "_model_module_version": "1.2.0", 644 | "_model_name": "LayoutModel", 645 | "_view_count": null, 646 | "_view_module": "@jupyter-widgets/base", 647 | "_view_module_version": "1.2.0", 648 | "_view_name": "LayoutView", 649 | "align_content": null, 650 | "align_items": null, 651 | "align_self": null, 652 | "border": null, 653 | "bottom": null, 654 | "display": null, 655 | "flex": null, 656 | "flex_flow": null, 657 | "grid_area": null, 658 | "grid_auto_columns": null, 659 | "grid_auto_flow": null, 660 | "grid_auto_rows": null, 661 | "grid_column": null, 662 | "grid_gap": null, 663 | "grid_row": null, 664 | "grid_template_areas": null, 665 | "grid_template_columns": null, 666 | "grid_template_rows": null, 667 | "height": null, 668 | "justify_content": null, 669 | "justify_items": null, 670 | "left": null, 671 | "margin": null, 672 | "max_height": null, 673 | "max_width": null, 674 | "min_height": null, 675 | "min_width": null, 676 | "object_fit": null, 677 | "object_position": null, 678 | "order": null, 679 | "overflow": null, 680 | "overflow_x": null, 681 | "overflow_y": null, 682 | "padding": null, 683 | "right": null, 684 | "top": null, 685 | "visibility": null, 686 | "width": null 687 | } 688 | }, 689 | "60198bd7296549bebfa02d030e153098": { 690 | "model_module": "@jupyter-widgets/controls", 691 | "model_name": "DescriptionStyleModel", 692 | "model_module_version": "1.5.0", 693 | "state": { 694 | "_model_module": "@jupyter-widgets/controls", 695 | "_model_module_version": "1.5.0", 696 | "_model_name": "DescriptionStyleModel", 697 | "_view_count": null, 698 | "_view_module": "@jupyter-widgets/base", 699 | "_view_module_version": "1.2.0", 700 | "_view_name": "StyleView", 701 | "description_width": "" 702 | } 703 | }, 704 | "3b2bd3bee32244a9a1598646e3c2ac96": { 705 | "model_module": "@jupyter-widgets/controls", 706 | "model_name": "HBoxModel", 707 | "model_module_version": "1.5.0", 708 | "state": { 709 | "_dom_classes": [], 710 | "_model_module": "@jupyter-widgets/controls", 711 | "_model_module_version": "1.5.0", 712 | "_model_name": "HBoxModel", 713 | "_view_count": null, 714 | "_view_module": "@jupyter-widgets/controls", 715 | "_view_module_version": "1.5.0", 716 | "_view_name": "HBoxView", 717 | "box_style": "", 718 | "children": [ 719 | "IPY_MODEL_d66e2e1d288944ed865c87cd0765ed9d", 720 | "IPY_MODEL_85116ccbf27442e5a8a94e03c4c1614a", 721 | "IPY_MODEL_194e7bb3f0b1470db38fca767afa4335" 722 | ], 723 | "layout": "IPY_MODEL_c25c400d86b04945a5e3590987aa903a" 724 | } 725 | }, 726 | "d66e2e1d288944ed865c87cd0765ed9d": { 727 | "model_module": "@jupyter-widgets/controls", 728 | "model_name": "HTMLModel", 729 | "model_module_version": "1.5.0", 730 | "state": { 731 | "_dom_classes": [], 732 | "_model_module": "@jupyter-widgets/controls", 733 | "_model_module_version": "1.5.0", 734 | "_model_name": "HTMLModel", 735 | "_view_count": null, 736 | "_view_module": "@jupyter-widgets/controls", 737 | "_view_module_version": "1.5.0", 738 | "_view_name": "HTMLView", 739 | "description": "", 740 | "description_tooltip": null, 741 | "layout": "IPY_MODEL_849bdeb13bce4cba820b1723735d86bd", 742 | "placeholder": "​", 743 | "style": "IPY_MODEL_8bb3faed90ef4db48f1506c026b0e4a3", 744 | "value": "vocab.txt: 100%" 745 | } 746 | }, 747 | "85116ccbf27442e5a8a94e03c4c1614a": { 748 | "model_module": "@jupyter-widgets/controls", 749 | "model_name": "FloatProgressModel", 750 | "model_module_version": "1.5.0", 751 | "state": { 752 | "_dom_classes": [], 753 | "_model_module": "@jupyter-widgets/controls", 754 | "_model_module_version": "1.5.0", 755 | "_model_name": "FloatProgressModel", 756 | "_view_count": null, 757 | "_view_module": "@jupyter-widgets/controls", 758 | "_view_module_version": "1.5.0", 759 | "_view_name": "ProgressView", 760 | "bar_style": "success", 761 | "description": "", 762 | "description_tooltip": null, 763 | "layout": "IPY_MODEL_a8fe0cc767cb435ca760cf5ca4967739", 764 | "max": 1195221, 765 | "min": 0, 766 | "orientation": "horizontal", 767 | "style": "IPY_MODEL_1041fabd9fc444499a432a7925437fda", 768 | "value": 1195221 769 | } 770 | }, 771 | "194e7bb3f0b1470db38fca767afa4335": { 772 | "model_module": "@jupyter-widgets/controls", 773 | "model_name": "HTMLModel", 774 | "model_module_version": "1.5.0", 775 | "state": { 776 | "_dom_classes": [], 777 | "_model_module": "@jupyter-widgets/controls", 778 | "_model_module_version": "1.5.0", 779 | "_model_name": "HTMLModel", 780 | "_view_count": null, 781 | "_view_module": "@jupyter-widgets/controls", 782 | "_view_module_version": "1.5.0", 783 | "_view_name": "HTMLView", 784 | "description": "", 785 | "description_tooltip": null, 786 | "layout": "IPY_MODEL_b539de3135df48a7802eefd75e08840d", 787 | "placeholder": "​", 788 | "style": "IPY_MODEL_caa9da2f3fef4c2b80a7ec7a4c169016", 789 | "value": " 1.20M/1.20M [00:00<00:00, 1.22MB/s]" 790 | } 791 | }, 792 | "c25c400d86b04945a5e3590987aa903a": { 793 | "model_module": "@jupyter-widgets/base", 794 | "model_name": "LayoutModel", 795 | "model_module_version": "1.2.0", 796 | "state": { 797 | "_model_module": "@jupyter-widgets/base", 798 | "_model_module_version": "1.2.0", 799 | "_model_name": "LayoutModel", 800 | "_view_count": null, 801 | "_view_module": "@jupyter-widgets/base", 802 | "_view_module_version": "1.2.0", 803 | "_view_name": "LayoutView", 804 | "align_content": null, 805 | "align_items": null, 806 | "align_self": null, 807 | "border": null, 808 | "bottom": null, 809 | "display": null, 810 | "flex": null, 811 | "flex_flow": null, 812 | "grid_area": null, 813 | "grid_auto_columns": null, 814 | "grid_auto_flow": null, 815 | "grid_auto_rows": null, 816 | "grid_column": null, 817 | "grid_gap": null, 818 | "grid_row": null, 819 | "grid_template_areas": null, 820 | "grid_template_columns": null, 821 | "grid_template_rows": null, 822 | "height": null, 823 | "justify_content": null, 824 | "justify_items": null, 825 | "left": null, 826 | "margin": null, 827 | "max_height": null, 828 | "max_width": null, 829 | "min_height": null, 830 | "min_width": null, 831 | "object_fit": null, 832 | "object_position": null, 833 | "order": null, 834 | "overflow": null, 835 | "overflow_x": null, 836 | "overflow_y": null, 837 | "padding": null, 838 | "right": null, 839 | "top": null, 840 | "visibility": null, 841 | "width": null 842 | } 843 | }, 844 | "849bdeb13bce4cba820b1723735d86bd": { 845 | "model_module": "@jupyter-widgets/base", 846 | "model_name": "LayoutModel", 847 | "model_module_version": "1.2.0", 848 | "state": { 849 | "_model_module": "@jupyter-widgets/base", 850 | "_model_module_version": "1.2.0", 851 | "_model_name": "LayoutModel", 852 | "_view_count": null, 853 | "_view_module": "@jupyter-widgets/base", 854 | "_view_module_version": "1.2.0", 855 | "_view_name": "LayoutView", 856 | "align_content": null, 857 | "align_items": null, 858 | "align_self": null, 859 | "border": null, 860 | "bottom": null, 861 | "display": null, 862 | "flex": null, 863 | "flex_flow": null, 864 | "grid_area": null, 865 | "grid_auto_columns": null, 866 | "grid_auto_flow": null, 867 | "grid_auto_rows": null, 868 | "grid_column": null, 869 | "grid_gap": null, 870 | "grid_row": null, 871 | "grid_template_areas": null, 872 | "grid_template_columns": null, 873 | "grid_template_rows": null, 874 | "height": null, 875 | "justify_content": null, 876 | "justify_items": null, 877 | "left": null, 878 | "margin": null, 879 | "max_height": null, 880 | "max_width": null, 881 | "min_height": null, 882 | "min_width": null, 883 | "object_fit": null, 884 | "object_position": null, 885 | "order": null, 886 | "overflow": null, 887 | "overflow_x": null, 888 | "overflow_y": null, 889 | "padding": null, 890 | "right": null, 891 | "top": null, 892 | "visibility": null, 893 | "width": null 894 | } 895 | }, 896 | "8bb3faed90ef4db48f1506c026b0e4a3": { 897 | "model_module": "@jupyter-widgets/controls", 898 | "model_name": "DescriptionStyleModel", 899 | "model_module_version": "1.5.0", 900 | "state": { 901 | "_model_module": "@jupyter-widgets/controls", 902 | "_model_module_version": "1.5.0", 903 | "_model_name": "DescriptionStyleModel", 904 | "_view_count": null, 905 | "_view_module": "@jupyter-widgets/base", 906 | "_view_module_version": "1.2.0", 907 | "_view_name": "StyleView", 908 | "description_width": "" 909 | } 910 | }, 911 | "a8fe0cc767cb435ca760cf5ca4967739": { 912 | "model_module": "@jupyter-widgets/base", 913 | "model_name": "LayoutModel", 914 | "model_module_version": "1.2.0", 915 | "state": { 916 | "_model_module": "@jupyter-widgets/base", 917 | "_model_module_version": "1.2.0", 918 | "_model_name": "LayoutModel", 919 | "_view_count": null, 920 | "_view_module": "@jupyter-widgets/base", 921 | "_view_module_version": "1.2.0", 922 | "_view_name": "LayoutView", 923 | "align_content": null, 924 | "align_items": null, 925 | "align_self": null, 926 | "border": null, 927 | "bottom": null, 928 | "display": null, 929 | "flex": null, 930 | "flex_flow": null, 931 | "grid_area": null, 932 | "grid_auto_columns": null, 933 | "grid_auto_flow": null, 934 | "grid_auto_rows": null, 935 | "grid_column": null, 936 | "grid_gap": null, 937 | "grid_row": null, 938 | "grid_template_areas": null, 939 | "grid_template_columns": null, 940 | "grid_template_rows": null, 941 | "height": null, 942 | "justify_content": null, 943 | "justify_items": null, 944 | "left": null, 945 | "margin": null, 946 | "max_height": null, 947 | "max_width": null, 948 | "min_height": null, 949 | "min_width": null, 950 | "object_fit": null, 951 | "object_position": null, 952 | "order": null, 953 | "overflow": null, 954 | "overflow_x": null, 955 | "overflow_y": null, 956 | "padding": null, 957 | "right": null, 958 | "top": null, 959 | "visibility": null, 960 | "width": null 961 | } 962 | }, 963 | "1041fabd9fc444499a432a7925437fda": { 964 | "model_module": "@jupyter-widgets/controls", 965 | "model_name": "ProgressStyleModel", 966 | "model_module_version": "1.5.0", 967 | "state": { 968 | "_model_module": "@jupyter-widgets/controls", 969 | "_model_module_version": "1.5.0", 970 | "_model_name": "ProgressStyleModel", 971 | "_view_count": null, 972 | "_view_module": "@jupyter-widgets/base", 973 | "_view_module_version": "1.2.0", 974 | "_view_name": "StyleView", 975 | "bar_color": null, 976 | "description_width": "" 977 | } 978 | }, 979 | "b539de3135df48a7802eefd75e08840d": { 980 | "model_module": "@jupyter-widgets/base", 981 | "model_name": "LayoutModel", 982 | "model_module_version": "1.2.0", 983 | "state": { 984 | "_model_module": "@jupyter-widgets/base", 985 | "_model_module_version": "1.2.0", 986 | "_model_name": "LayoutModel", 987 | "_view_count": null, 988 | "_view_module": "@jupyter-widgets/base", 989 | "_view_module_version": "1.2.0", 990 | "_view_name": "LayoutView", 991 | "align_content": null, 992 | "align_items": null, 993 | "align_self": null, 994 | "border": null, 995 | "bottom": null, 996 | "display": null, 997 | "flex": null, 998 | "flex_flow": null, 999 | "grid_area": null, 1000 | "grid_auto_columns": null, 1001 | "grid_auto_flow": null, 1002 | "grid_auto_rows": null, 1003 | "grid_column": null, 1004 | "grid_gap": null, 1005 | "grid_row": null, 1006 | "grid_template_areas": null, 1007 | "grid_template_columns": null, 1008 | "grid_template_rows": null, 1009 | "height": null, 1010 | "justify_content": null, 1011 | "justify_items": null, 1012 | "left": null, 1013 | "margin": null, 1014 | "max_height": null, 1015 | "max_width": null, 1016 | "min_height": null, 1017 | "min_width": null, 1018 | "object_fit": null, 1019 | "object_position": null, 1020 | "order": null, 1021 | "overflow": null, 1022 | "overflow_x": null, 1023 | "overflow_y": null, 1024 | "padding": null, 1025 | "right": null, 1026 | "top": null, 1027 | "visibility": null, 1028 | "width": null 1029 | } 1030 | }, 1031 | "caa9da2f3fef4c2b80a7ec7a4c169016": { 1032 | "model_module": "@jupyter-widgets/controls", 1033 | "model_name": "DescriptionStyleModel", 1034 | "model_module_version": "1.5.0", 1035 | "state": { 1036 | "_model_module": "@jupyter-widgets/controls", 1037 | "_model_module_version": "1.5.0", 1038 | "_model_name": "DescriptionStyleModel", 1039 | "_view_count": null, 1040 | "_view_module": "@jupyter-widgets/base", 1041 | "_view_module_version": "1.2.0", 1042 | "_view_name": "StyleView", 1043 | "description_width": "" 1044 | } 1045 | }, 1046 | "517fb97311cd469288edb7165b504911": { 1047 | "model_module": "@jupyter-widgets/controls", 1048 | "model_name": "HBoxModel", 1049 | "model_module_version": "1.5.0", 1050 | "state": { 1051 | "_dom_classes": [], 1052 | "_model_module": "@jupyter-widgets/controls", 1053 | "_model_module_version": "1.5.0", 1054 | "_model_name": "HBoxModel", 1055 | "_view_count": null, 1056 | "_view_module": "@jupyter-widgets/controls", 1057 | "_view_module_version": "1.5.0", 1058 | "_view_name": "HBoxView", 1059 | "box_style": "", 1060 | "children": [ 1061 | "IPY_MODEL_e6ab54cafbb54107b1052b9879121e3d", 1062 | "IPY_MODEL_94a63d2944214eca97079a9bb1bea55d", 1063 | "IPY_MODEL_30cfb45cf5404cc1aaf45515c0958d8a" 1064 | ], 1065 | "layout": "IPY_MODEL_d4bbc6623727407589577b3e7122657e" 1066 | } 1067 | }, 1068 | "e6ab54cafbb54107b1052b9879121e3d": { 1069 | "model_module": "@jupyter-widgets/controls", 1070 | "model_name": "HTMLModel", 1071 | "model_module_version": "1.5.0", 1072 | "state": { 1073 | "_dom_classes": [], 1074 | "_model_module": "@jupyter-widgets/controls", 1075 | "_model_module_version": "1.5.0", 1076 | "_model_name": "HTMLModel", 1077 | "_view_count": null, 1078 | "_view_module": "@jupyter-widgets/controls", 1079 | "_view_module_version": "1.5.0", 1080 | "_view_name": "HTMLView", 1081 | "description": "", 1082 | "description_tooltip": null, 1083 | "layout": "IPY_MODEL_9ace909a29fd45b2bb3aa647d75e3965", 1084 | "placeholder": "​", 1085 | "style": "IPY_MODEL_8c2d8871cd2f47eabd231a7cc5ed339a", 1086 | "value": "emoji.json: 100%" 1087 | } 1088 | }, 1089 | "94a63d2944214eca97079a9bb1bea55d": { 1090 | "model_module": "@jupyter-widgets/controls", 1091 | "model_name": "FloatProgressModel", 1092 | "model_module_version": "1.5.0", 1093 | "state": { 1094 | "_dom_classes": [], 1095 | "_model_module": "@jupyter-widgets/controls", 1096 | "_model_module_version": "1.5.0", 1097 | "_model_name": "FloatProgressModel", 1098 | "_view_count": null, 1099 | "_view_module": "@jupyter-widgets/controls", 1100 | "_view_module_version": "1.5.0", 1101 | "_view_name": "ProgressView", 1102 | "bar_style": "success", 1103 | "description": "", 1104 | "description_tooltip": null, 1105 | "layout": "IPY_MODEL_83579b1e91eb4385b8ddcfda2c717473", 1106 | "max": 189183, 1107 | "min": 0, 1108 | "orientation": "horizontal", 1109 | "style": "IPY_MODEL_cf039b27f8a74b1497ed51b0deababef", 1110 | "value": 189183 1111 | } 1112 | }, 1113 | "30cfb45cf5404cc1aaf45515c0958d8a": { 1114 | "model_module": "@jupyter-widgets/controls", 1115 | "model_name": "HTMLModel", 1116 | "model_module_version": "1.5.0", 1117 | "state": { 1118 | "_dom_classes": [], 1119 | "_model_module": "@jupyter-widgets/controls", 1120 | "_model_module_version": "1.5.0", 1121 | "_model_name": "HTMLModel", 1122 | "_view_count": null, 1123 | "_view_module": "@jupyter-widgets/controls", 1124 | "_view_module_version": "1.5.0", 1125 | "_view_name": "HTMLView", 1126 | "description": "", 1127 | "description_tooltip": null, 1128 | "layout": "IPY_MODEL_e8797cf313af43b3958e502fcd2f817b", 1129 | "placeholder": "​", 1130 | "style": "IPY_MODEL_113aca6991c142de8e28737239af0803", 1131 | "value": " 189k/189k [00:00<00:00, 486kB/s]" 1132 | } 1133 | }, 1134 | "d4bbc6623727407589577b3e7122657e": { 1135 | "model_module": "@jupyter-widgets/base", 1136 | "model_name": "LayoutModel", 1137 | "model_module_version": "1.2.0", 1138 | "state": { 1139 | "_model_module": "@jupyter-widgets/base", 1140 | "_model_module_version": "1.2.0", 1141 | "_model_name": "LayoutModel", 1142 | "_view_count": null, 1143 | "_view_module": "@jupyter-widgets/base", 1144 | "_view_module_version": "1.2.0", 1145 | "_view_name": "LayoutView", 1146 | "align_content": null, 1147 | "align_items": null, 1148 | "align_self": null, 1149 | "border": null, 1150 | "bottom": null, 1151 | "display": null, 1152 | "flex": null, 1153 | "flex_flow": null, 1154 | "grid_area": null, 1155 | "grid_auto_columns": null, 1156 | "grid_auto_flow": null, 1157 | "grid_auto_rows": null, 1158 | "grid_column": null, 1159 | "grid_gap": null, 1160 | "grid_row": null, 1161 | "grid_template_areas": null, 1162 | "grid_template_columns": null, 1163 | "grid_template_rows": null, 1164 | "height": null, 1165 | "justify_content": null, 1166 | "justify_items": null, 1167 | "left": null, 1168 | "margin": null, 1169 | "max_height": null, 1170 | "max_width": null, 1171 | "min_height": null, 1172 | "min_width": null, 1173 | "object_fit": null, 1174 | "object_position": null, 1175 | "order": null, 1176 | "overflow": null, 1177 | "overflow_x": null, 1178 | "overflow_y": null, 1179 | "padding": null, 1180 | "right": null, 1181 | "top": null, 1182 | "visibility": null, 1183 | "width": null 1184 | } 1185 | }, 1186 | "9ace909a29fd45b2bb3aa647d75e3965": { 1187 | "model_module": "@jupyter-widgets/base", 1188 | "model_name": "LayoutModel", 1189 | "model_module_version": "1.2.0", 1190 | "state": { 1191 | "_model_module": "@jupyter-widgets/base", 1192 | "_model_module_version": "1.2.0", 1193 | "_model_name": "LayoutModel", 1194 | "_view_count": null, 1195 | "_view_module": "@jupyter-widgets/base", 1196 | "_view_module_version": "1.2.0", 1197 | "_view_name": "LayoutView", 1198 | "align_content": null, 1199 | "align_items": null, 1200 | "align_self": null, 1201 | "border": null, 1202 | "bottom": null, 1203 | "display": null, 1204 | "flex": null, 1205 | "flex_flow": null, 1206 | "grid_area": null, 1207 | "grid_auto_columns": null, 1208 | "grid_auto_flow": null, 1209 | "grid_auto_rows": null, 1210 | "grid_column": null, 1211 | "grid_gap": null, 1212 | "grid_row": null, 1213 | "grid_template_areas": null, 1214 | "grid_template_columns": null, 1215 | "grid_template_rows": null, 1216 | "height": null, 1217 | "justify_content": null, 1218 | "justify_items": null, 1219 | "left": null, 1220 | "margin": null, 1221 | "max_height": null, 1222 | "max_width": null, 1223 | "min_height": null, 1224 | "min_width": null, 1225 | "object_fit": null, 1226 | "object_position": null, 1227 | "order": null, 1228 | "overflow": null, 1229 | "overflow_x": null, 1230 | "overflow_y": null, 1231 | "padding": null, 1232 | "right": null, 1233 | "top": null, 1234 | "visibility": null, 1235 | "width": null 1236 | } 1237 | }, 1238 | "8c2d8871cd2f47eabd231a7cc5ed339a": { 1239 | "model_module": "@jupyter-widgets/controls", 1240 | "model_name": "DescriptionStyleModel", 1241 | "model_module_version": "1.5.0", 1242 | "state": { 1243 | "_model_module": "@jupyter-widgets/controls", 1244 | "_model_module_version": "1.5.0", 1245 | "_model_name": "DescriptionStyleModel", 1246 | "_view_count": null, 1247 | "_view_module": "@jupyter-widgets/base", 1248 | "_view_module_version": "1.2.0", 1249 | "_view_name": "StyleView", 1250 | "description_width": "" 1251 | } 1252 | }, 1253 | "83579b1e91eb4385b8ddcfda2c717473": { 1254 | "model_module": "@jupyter-widgets/base", 1255 | "model_name": "LayoutModel", 1256 | "model_module_version": "1.2.0", 1257 | "state": { 1258 | "_model_module": "@jupyter-widgets/base", 1259 | "_model_module_version": "1.2.0", 1260 | "_model_name": "LayoutModel", 1261 | "_view_count": null, 1262 | "_view_module": "@jupyter-widgets/base", 1263 | "_view_module_version": "1.2.0", 1264 | "_view_name": "LayoutView", 1265 | "align_content": null, 1266 | "align_items": null, 1267 | "align_self": null, 1268 | "border": null, 1269 | "bottom": null, 1270 | "display": null, 1271 | "flex": null, 1272 | "flex_flow": null, 1273 | "grid_area": null, 1274 | "grid_auto_columns": null, 1275 | "grid_auto_flow": null, 1276 | "grid_auto_rows": null, 1277 | "grid_column": null, 1278 | "grid_gap": null, 1279 | "grid_row": null, 1280 | "grid_template_areas": null, 1281 | "grid_template_columns": null, 1282 | "grid_template_rows": null, 1283 | "height": null, 1284 | "justify_content": null, 1285 | "justify_items": null, 1286 | "left": null, 1287 | "margin": null, 1288 | "max_height": null, 1289 | "max_width": null, 1290 | "min_height": null, 1291 | "min_width": null, 1292 | "object_fit": null, 1293 | "object_position": null, 1294 | "order": null, 1295 | "overflow": null, 1296 | "overflow_x": null, 1297 | "overflow_y": null, 1298 | "padding": null, 1299 | "right": null, 1300 | "top": null, 1301 | "visibility": null, 1302 | "width": null 1303 | } 1304 | }, 1305 | "cf039b27f8a74b1497ed51b0deababef": { 1306 | "model_module": "@jupyter-widgets/controls", 1307 | "model_name": "ProgressStyleModel", 1308 | "model_module_version": "1.5.0", 1309 | "state": { 1310 | "_model_module": "@jupyter-widgets/controls", 1311 | "_model_module_version": "1.5.0", 1312 | "_model_name": "ProgressStyleModel", 1313 | "_view_count": null, 1314 | "_view_module": "@jupyter-widgets/base", 1315 | "_view_module_version": "1.2.0", 1316 | "_view_name": "StyleView", 1317 | "bar_color": null, 1318 | "description_width": "" 1319 | } 1320 | }, 1321 | "e8797cf313af43b3958e502fcd2f817b": { 1322 | "model_module": "@jupyter-widgets/base", 1323 | "model_name": "LayoutModel", 1324 | "model_module_version": "1.2.0", 1325 | "state": { 1326 | "_model_module": "@jupyter-widgets/base", 1327 | "_model_module_version": "1.2.0", 1328 | "_model_name": "LayoutModel", 1329 | "_view_count": null, 1330 | "_view_module": "@jupyter-widgets/base", 1331 | "_view_module_version": "1.2.0", 1332 | "_view_name": "LayoutView", 1333 | "align_content": null, 1334 | "align_items": null, 1335 | "align_self": null, 1336 | "border": null, 1337 | "bottom": null, 1338 | "display": null, 1339 | "flex": null, 1340 | "flex_flow": null, 1341 | "grid_area": null, 1342 | "grid_auto_columns": null, 1343 | "grid_auto_flow": null, 1344 | "grid_auto_rows": null, 1345 | "grid_column": null, 1346 | "grid_gap": null, 1347 | "grid_row": null, 1348 | "grid_template_areas": null, 1349 | "grid_template_columns": null, 1350 | "grid_template_rows": null, 1351 | "height": null, 1352 | "justify_content": null, 1353 | "justify_items": null, 1354 | "left": null, 1355 | "margin": null, 1356 | "max_height": null, 1357 | "max_width": null, 1358 | "min_height": null, 1359 | "min_width": null, 1360 | "object_fit": null, 1361 | "object_position": null, 1362 | "order": null, 1363 | "overflow": null, 1364 | "overflow_x": null, 1365 | "overflow_y": null, 1366 | "padding": null, 1367 | "right": null, 1368 | "top": null, 1369 | "visibility": null, 1370 | "width": null 1371 | } 1372 | }, 1373 | "113aca6991c142de8e28737239af0803": { 1374 | "model_module": "@jupyter-widgets/controls", 1375 | "model_name": "DescriptionStyleModel", 1376 | "model_module_version": "1.5.0", 1377 | "state": { 1378 | "_model_module": "@jupyter-widgets/controls", 1379 | "_model_module_version": "1.5.0", 1380 | "_model_name": "DescriptionStyleModel", 1381 | "_view_count": null, 1382 | "_view_module": "@jupyter-widgets/base", 1383 | "_view_module_version": "1.2.0", 1384 | "_view_name": "StyleView", 1385 | "description_width": "" 1386 | } 1387 | }, 1388 | "b62471ed416e41c4b9ca16b3fe6fee35": { 1389 | "model_module": "@jupyter-widgets/controls", 1390 | "model_name": "HBoxModel", 1391 | "model_module_version": "1.5.0", 1392 | "state": { 1393 | "_dom_classes": [], 1394 | "_model_module": "@jupyter-widgets/controls", 1395 | "_model_module_version": "1.5.0", 1396 | "_model_name": "HBoxModel", 1397 | "_view_count": null, 1398 | "_view_module": "@jupyter-widgets/controls", 1399 | "_view_module_version": "1.5.0", 1400 | "_view_name": "HBoxView", 1401 | "box_style": "", 1402 | "children": [ 1403 | "IPY_MODEL_a3319fd213ed4c66b2aef3236904b578", 1404 | "IPY_MODEL_a262135eff97435c938cd61b3b576e55", 1405 | "IPY_MODEL_8b74ab4a9d824881ba1b17cdeb7bf75c" 1406 | ], 1407 | "layout": "IPY_MODEL_d19cbadaa6f648098b30fd7cab88143b" 1408 | } 1409 | }, 1410 | "a3319fd213ed4c66b2aef3236904b578": { 1411 | "model_module": "@jupyter-widgets/controls", 1412 | "model_name": "HTMLModel", 1413 | "model_module_version": "1.5.0", 1414 | "state": { 1415 | "_dom_classes": [], 1416 | "_model_module": "@jupyter-widgets/controls", 1417 | "_model_module_version": "1.5.0", 1418 | "_model_name": "HTMLModel", 1419 | "_view_count": null, 1420 | "_view_module": "@jupyter-widgets/controls", 1421 | "_view_module_version": "1.5.0", 1422 | "_view_name": "HTMLView", 1423 | "description": "", 1424 | "description_tooltip": null, 1425 | "layout": "IPY_MODEL_44b6ebe9c3d942d48c867e1425e22bba", 1426 | "placeholder": "​", 1427 | "style": "IPY_MODEL_ee40d822c7a44a77ac0dd1ddb403d44a", 1428 | "value": "pytorch_model.bin: 100%" 1429 | } 1430 | }, 1431 | "a262135eff97435c938cd61b3b576e55": { 1432 | "model_module": "@jupyter-widgets/controls", 1433 | "model_name": "FloatProgressModel", 1434 | "model_module_version": "1.5.0", 1435 | "state": { 1436 | "_dom_classes": [], 1437 | "_model_module": "@jupyter-widgets/controls", 1438 | "_model_module_version": "1.5.0", 1439 | "_model_name": "FloatProgressModel", 1440 | "_view_count": null, 1441 | "_view_module": "@jupyter-widgets/controls", 1442 | "_view_module_version": "1.5.0", 1443 | "_view_name": "ProgressView", 1444 | "bar_style": "success", 1445 | "description": "", 1446 | "description_tooltip": null, 1447 | "layout": "IPY_MODEL_cf3a649bbddd4da691341f967e93f377", 1448 | "max": 5361640123, 1449 | "min": 0, 1450 | "orientation": "horizontal", 1451 | "style": "IPY_MODEL_e979f667255f432abe04bfebc2ff3418", 1452 | "value": 5361640123 1453 | } 1454 | }, 1455 | "8b74ab4a9d824881ba1b17cdeb7bf75c": { 1456 | "model_module": "@jupyter-widgets/controls", 1457 | "model_name": "HTMLModel", 1458 | "model_module_version": "1.5.0", 1459 | "state": { 1460 | "_dom_classes": [], 1461 | "_model_module": "@jupyter-widgets/controls", 1462 | "_model_module_version": "1.5.0", 1463 | "_model_name": "HTMLModel", 1464 | "_view_count": null, 1465 | "_view_module": "@jupyter-widgets/controls", 1466 | "_view_module_version": "1.5.0", 1467 | "_view_name": "HTMLView", 1468 | "description": "", 1469 | "description_tooltip": null, 1470 | "layout": "IPY_MODEL_1582c2d1fd674f4986798272a169bba2", 1471 | "placeholder": "​", 1472 | "style": "IPY_MODEL_143ea22cea6d4530947ce1986a4c61ac", 1473 | "value": " 5.36G/5.36G [04:37<00:00, 19.0MB/s]" 1474 | } 1475 | }, 1476 | "d19cbadaa6f648098b30fd7cab88143b": { 1477 | "model_module": "@jupyter-widgets/base", 1478 | "model_name": "LayoutModel", 1479 | "model_module_version": "1.2.0", 1480 | "state": { 1481 | "_model_module": "@jupyter-widgets/base", 1482 | "_model_module_version": "1.2.0", 1483 | "_model_name": "LayoutModel", 1484 | "_view_count": null, 1485 | "_view_module": "@jupyter-widgets/base", 1486 | "_view_module_version": "1.2.0", 1487 | "_view_name": "LayoutView", 1488 | "align_content": null, 1489 | "align_items": null, 1490 | "align_self": null, 1491 | "border": null, 1492 | "bottom": null, 1493 | "display": null, 1494 | "flex": null, 1495 | "flex_flow": null, 1496 | "grid_area": null, 1497 | "grid_auto_columns": null, 1498 | "grid_auto_flow": null, 1499 | "grid_auto_rows": null, 1500 | "grid_column": null, 1501 | "grid_gap": null, 1502 | "grid_row": null, 1503 | "grid_template_areas": null, 1504 | "grid_template_columns": null, 1505 | "grid_template_rows": null, 1506 | "height": null, 1507 | "justify_content": null, 1508 | "justify_items": null, 1509 | "left": null, 1510 | "margin": null, 1511 | "max_height": null, 1512 | "max_width": null, 1513 | "min_height": null, 1514 | "min_width": null, 1515 | "object_fit": null, 1516 | "object_position": null, 1517 | "order": null, 1518 | "overflow": null, 1519 | "overflow_x": null, 1520 | "overflow_y": null, 1521 | "padding": null, 1522 | "right": null, 1523 | "top": null, 1524 | "visibility": null, 1525 | "width": null 1526 | } 1527 | }, 1528 | "44b6ebe9c3d942d48c867e1425e22bba": { 1529 | "model_module": "@jupyter-widgets/base", 1530 | "model_name": "LayoutModel", 1531 | "model_module_version": "1.2.0", 1532 | "state": { 1533 | "_model_module": "@jupyter-widgets/base", 1534 | "_model_module_version": "1.2.0", 1535 | "_model_name": "LayoutModel", 1536 | "_view_count": null, 1537 | "_view_module": "@jupyter-widgets/base", 1538 | "_view_module_version": "1.2.0", 1539 | "_view_name": "LayoutView", 1540 | "align_content": null, 1541 | "align_items": null, 1542 | "align_self": null, 1543 | "border": null, 1544 | "bottom": null, 1545 | "display": null, 1546 | "flex": null, 1547 | "flex_flow": null, 1548 | "grid_area": null, 1549 | "grid_auto_columns": null, 1550 | "grid_auto_flow": null, 1551 | "grid_auto_rows": null, 1552 | "grid_column": null, 1553 | "grid_gap": null, 1554 | "grid_row": null, 1555 | "grid_template_areas": null, 1556 | "grid_template_columns": null, 1557 | "grid_template_rows": null, 1558 | "height": null, 1559 | "justify_content": null, 1560 | "justify_items": null, 1561 | "left": null, 1562 | "margin": null, 1563 | "max_height": null, 1564 | "max_width": null, 1565 | "min_height": null, 1566 | "min_width": null, 1567 | "object_fit": null, 1568 | "object_position": null, 1569 | "order": null, 1570 | "overflow": null, 1571 | "overflow_x": null, 1572 | "overflow_y": null, 1573 | "padding": null, 1574 | "right": null, 1575 | "top": null, 1576 | "visibility": null, 1577 | "width": null 1578 | } 1579 | }, 1580 | "ee40d822c7a44a77ac0dd1ddb403d44a": { 1581 | "model_module": "@jupyter-widgets/controls", 1582 | "model_name": "DescriptionStyleModel", 1583 | "model_module_version": "1.5.0", 1584 | "state": { 1585 | "_model_module": "@jupyter-widgets/controls", 1586 | "_model_module_version": "1.5.0", 1587 | "_model_name": "DescriptionStyleModel", 1588 | "_view_count": null, 1589 | "_view_module": "@jupyter-widgets/base", 1590 | "_view_module_version": "1.2.0", 1591 | "_view_name": "StyleView", 1592 | "description_width": "" 1593 | } 1594 | }, 1595 | "cf3a649bbddd4da691341f967e93f377": { 1596 | "model_module": "@jupyter-widgets/base", 1597 | "model_name": "LayoutModel", 1598 | "model_module_version": "1.2.0", 1599 | "state": { 1600 | "_model_module": "@jupyter-widgets/base", 1601 | "_model_module_version": "1.2.0", 1602 | "_model_name": "LayoutModel", 1603 | "_view_count": null, 1604 | "_view_module": "@jupyter-widgets/base", 1605 | "_view_module_version": "1.2.0", 1606 | "_view_name": "LayoutView", 1607 | "align_content": null, 1608 | "align_items": null, 1609 | "align_self": null, 1610 | "border": null, 1611 | "bottom": null, 1612 | "display": null, 1613 | "flex": null, 1614 | "flex_flow": null, 1615 | "grid_area": null, 1616 | "grid_auto_columns": null, 1617 | "grid_auto_flow": null, 1618 | "grid_auto_rows": null, 1619 | "grid_column": null, 1620 | "grid_gap": null, 1621 | "grid_row": null, 1622 | "grid_template_areas": null, 1623 | "grid_template_columns": null, 1624 | "grid_template_rows": null, 1625 | "height": null, 1626 | "justify_content": null, 1627 | "justify_items": null, 1628 | "left": null, 1629 | "margin": null, 1630 | "max_height": null, 1631 | "max_width": null, 1632 | "min_height": null, 1633 | "min_width": null, 1634 | "object_fit": null, 1635 | "object_position": null, 1636 | "order": null, 1637 | "overflow": null, 1638 | "overflow_x": null, 1639 | "overflow_y": null, 1640 | "padding": null, 1641 | "right": null, 1642 | "top": null, 1643 | "visibility": null, 1644 | "width": null 1645 | } 1646 | }, 1647 | "e979f667255f432abe04bfebc2ff3418": { 1648 | "model_module": "@jupyter-widgets/controls", 1649 | "model_name": "ProgressStyleModel", 1650 | "model_module_version": "1.5.0", 1651 | "state": { 1652 | "_model_module": "@jupyter-widgets/controls", 1653 | "_model_module_version": "1.5.0", 1654 | "_model_name": "ProgressStyleModel", 1655 | "_view_count": null, 1656 | "_view_module": "@jupyter-widgets/base", 1657 | "_view_module_version": "1.2.0", 1658 | "_view_name": "StyleView", 1659 | "bar_color": null, 1660 | "description_width": "" 1661 | } 1662 | }, 1663 | "1582c2d1fd674f4986798272a169bba2": { 1664 | "model_module": "@jupyter-widgets/base", 1665 | "model_name": "LayoutModel", 1666 | "model_module_version": "1.2.0", 1667 | "state": { 1668 | "_model_module": "@jupyter-widgets/base", 1669 | "_model_module_version": "1.2.0", 1670 | "_model_name": "LayoutModel", 1671 | "_view_count": null, 1672 | "_view_module": "@jupyter-widgets/base", 1673 | "_view_module_version": "1.2.0", 1674 | "_view_name": "LayoutView", 1675 | "align_content": null, 1676 | "align_items": null, 1677 | "align_self": null, 1678 | "border": null, 1679 | "bottom": null, 1680 | "display": null, 1681 | "flex": null, 1682 | "flex_flow": null, 1683 | "grid_area": null, 1684 | "grid_auto_columns": null, 1685 | "grid_auto_flow": null, 1686 | "grid_auto_rows": null, 1687 | "grid_column": null, 1688 | "grid_gap": null, 1689 | "grid_row": null, 1690 | "grid_template_areas": null, 1691 | "grid_template_columns": null, 1692 | "grid_template_rows": null, 1693 | "height": null, 1694 | "justify_content": null, 1695 | "justify_items": null, 1696 | "left": null, 1697 | "margin": null, 1698 | "max_height": null, 1699 | "max_width": null, 1700 | "min_height": null, 1701 | "min_width": null, 1702 | "object_fit": null, 1703 | "object_position": null, 1704 | "order": null, 1705 | "overflow": null, 1706 | "overflow_x": null, 1707 | "overflow_y": null, 1708 | "padding": null, 1709 | "right": null, 1710 | "top": null, 1711 | "visibility": null, 1712 | "width": null 1713 | } 1714 | }, 1715 | "143ea22cea6d4530947ce1986a4c61ac": { 1716 | "model_module": "@jupyter-widgets/controls", 1717 | "model_name": "DescriptionStyleModel", 1718 | "model_module_version": "1.5.0", 1719 | "state": { 1720 | "_model_module": "@jupyter-widgets/controls", 1721 | "_model_module_version": "1.5.0", 1722 | "_model_name": "DescriptionStyleModel", 1723 | "_view_count": null, 1724 | "_view_module": "@jupyter-widgets/base", 1725 | "_view_module_version": "1.2.0", 1726 | "_view_name": "StyleView", 1727 | "description_width": "" 1728 | } 1729 | } 1730 | } 1731 | } 1732 | }, 1733 | "cells": [ 1734 | { 1735 | "cell_type": "markdown", 1736 | "metadata": { 1737 | "id": "view-in-github", 1738 | "colab_type": "text" 1739 | }, 1740 | "source": [ 1741 | "\"Open" 1742 | ] 1743 | }, 1744 | { 1745 | "cell_type": "code", 1746 | "execution_count": 1, 1747 | "metadata": { 1748 | "colab": { 1749 | "base_uri": "https://localhost:8080/" 1750 | }, 1751 | "id": "NKvtUsBuTpDm", 1752 | "outputId": "dbc07c80-f8b6-4007-bc25-281db76bac72" 1753 | }, 1754 | "outputs": [ 1755 | { 1756 | "output_type": "stream", 1757 | "name": "stdout", 1758 | "text": [ 1759 | "Requirement already satisfied: transformers in /usr/local/lib/python3.10/dist-packages (4.35.2)\n", 1760 | "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from transformers) (3.13.1)\n", 1761 | "Requirement already satisfied: huggingface-hub<1.0,>=0.16.4 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.19.4)\n", 1762 | "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (1.23.5)\n", 1763 | "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from transformers) (23.2)\n", 1764 | "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (6.0.1)\n", 1765 | "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (2023.6.3)\n", 1766 | "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from transformers) (2.31.0)\n", 1767 | "Requirement already satisfied: tokenizers<0.19,>=0.14 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.15.0)\n", 1768 | "Requirement already satisfied: safetensors>=0.3.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.4.1)\n", 1769 | "Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.10/dist-packages (from transformers) (4.66.1)\n", 1770 | "Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.16.4->transformers) (2023.6.0)\n", 1771 | "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.16.4->transformers) (4.5.0)\n", 1772 | "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (3.3.2)\n", 1773 | "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (3.6)\n", 1774 | "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2.0.7)\n", 1775 | "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2023.11.17)\n" 1776 | ] 1777 | } 1778 | ], 1779 | "source": [ 1780 | "!pip install transformers" 1781 | ] 1782 | }, 1783 | { 1784 | "cell_type": "code", 1785 | "source": [ 1786 | "import torch\n", 1787 | "from transformers import AutoTokenizer, AutoModelForCausalLM\n", 1788 | "\n", 1789 | "# トークナイザーとモデルの準備\n", 1790 | "tokenizer = AutoTokenizer.from_pretrained(\n", 1791 | " \"abeja/gpt-neox-japanese-2.7b\",\n", 1792 | ")\n", 1793 | "model = AutoModelForCausalLM.from_pretrained(\n", 1794 | " \"abeja/gpt-neox-japanese-2.7b\"\n", 1795 | ")" 1796 | ], 1797 | "metadata": { 1798 | "colab": { 1799 | "base_uri": "https://localhost:8080/", 1800 | "height": 177, 1801 | "referenced_widgets": [ 1802 | "7e2fa68518be449f80fd97746305eab0", 1803 | "9c9a672fc7b6408c8f36eb48be24257f", 1804 | "a1ac3cff06d3416db0b8c9dd9edf48f5", 1805 | "f1a3e3ef130348d0877668ad50382a78", 1806 | "19de596f8f60498c908b3adf9d34cd41", 1807 | "04d35b3697a44e58a57ead48479a1a73", 1808 | "c14afb7238044f25ac888f750979ab26", 1809 | "3853ef77d1eb43aeb44cdb44b79b79c3", 1810 | "97f29a72eda4407b880c17da8a4c54e3", 1811 | "48f2ee42333243978c5f21f68c242631", 1812 | "ef0c0287d1674492a2bd79e38a32f639", 1813 | "7aabeac5f94d45938c70d85d5f6030e2", 1814 | "6cb27ec0214d4fe38cae4d09ea5146ee", 1815 | "d5547266057f45a8b9ae0b88d553fc1f", 1816 | "be5c4d04beeb43a2b2da1f7aa1fd3c3d", 1817 | "80d12bc12f194e8aaee9273af820d2a7", 1818 | "915790952c444556b003d7295d1c5ccb", 1819 | "b26c3ac3150c46c6853f08a40c88e234", 1820 | "4133abb3166e49fa9d1f851d97d15741", 1821 | "183c7fbb1b464b7fbdc37f1042def7df", 1822 | "2f7a0c6355ef48669b8889a0cdc86d30", 1823 | "60198bd7296549bebfa02d030e153098", 1824 | "3b2bd3bee32244a9a1598646e3c2ac96", 1825 | "d66e2e1d288944ed865c87cd0765ed9d", 1826 | "85116ccbf27442e5a8a94e03c4c1614a", 1827 | "194e7bb3f0b1470db38fca767afa4335", 1828 | "c25c400d86b04945a5e3590987aa903a", 1829 | "849bdeb13bce4cba820b1723735d86bd", 1830 | "8bb3faed90ef4db48f1506c026b0e4a3", 1831 | "a8fe0cc767cb435ca760cf5ca4967739", 1832 | "1041fabd9fc444499a432a7925437fda", 1833 | "b539de3135df48a7802eefd75e08840d", 1834 | "caa9da2f3fef4c2b80a7ec7a4c169016", 1835 | "517fb97311cd469288edb7165b504911", 1836 | "e6ab54cafbb54107b1052b9879121e3d", 1837 | "94a63d2944214eca97079a9bb1bea55d", 1838 | "30cfb45cf5404cc1aaf45515c0958d8a", 1839 | "d4bbc6623727407589577b3e7122657e", 1840 | "9ace909a29fd45b2bb3aa647d75e3965", 1841 | "8c2d8871cd2f47eabd231a7cc5ed339a", 1842 | "83579b1e91eb4385b8ddcfda2c717473", 1843 | "cf039b27f8a74b1497ed51b0deababef", 1844 | "e8797cf313af43b3958e502fcd2f817b", 1845 | "113aca6991c142de8e28737239af0803", 1846 | "b62471ed416e41c4b9ca16b3fe6fee35", 1847 | "a3319fd213ed4c66b2aef3236904b578", 1848 | "a262135eff97435c938cd61b3b576e55", 1849 | "8b74ab4a9d824881ba1b17cdeb7bf75c", 1850 | "d19cbadaa6f648098b30fd7cab88143b", 1851 | "44b6ebe9c3d942d48c867e1425e22bba", 1852 | "ee40d822c7a44a77ac0dd1ddb403d44a", 1853 | "cf3a649bbddd4da691341f967e93f377", 1854 | "e979f667255f432abe04bfebc2ff3418", 1855 | "1582c2d1fd674f4986798272a169bba2", 1856 | "143ea22cea6d4530947ce1986a4c61ac" 1857 | ] 1858 | }, 1859 | "id": "uNP4yIYxTunE", 1860 | "outputId": "1d677e19-fbdf-43b6-9d07-d2e54bb19377" 1861 | }, 1862 | "execution_count": 2, 1863 | "outputs": [ 1864 | { 1865 | "output_type": "display_data", 1866 | "data": { 1867 | "text/plain": [ 1868 | "tokenizer_config.json: 0%| | 0.00/168 [00:00\"Open" 30 | ] 31 | }, 32 | { 33 | "cell_type": "code", 34 | "execution_count": 1, 35 | "metadata": { 36 | "colab": { 37 | "base_uri": "https://localhost:8080/" 38 | }, 39 | "id": "JlCuBUApQa-7", 40 | "outputId": "2fa10acb-0469-4e68-ce0e-97d1f23c3efa" 41 | }, 42 | "outputs": [ 43 | { 44 | "output_type": "stream", 45 | "name": "stdout", 46 | "text": [ 47 | "Mounted at /content/drive\n" 48 | ] 49 | } 50 | ], 51 | "source": [ 52 | "# Googleドライブのマウント\n", 53 | "from google.colab import drive\n", 54 | "drive.mount(\"/content/drive\")" 55 | ] 56 | }, 57 | { 58 | "cell_type": "code", 59 | "source": [ 60 | "!git clone https://github.com/kohya-ss/sd-scripts\n", 61 | "%cd sd-scripts" 62 | ], 63 | "metadata": { 64 | "colab": { 65 | "base_uri": "https://localhost:8080/" 66 | }, 67 | "id": "QD8tvKa7Qggq", 68 | "outputId": "941efd0b-f4f8-42d8-f03c-c3f8566efabf" 69 | }, 70 | "execution_count": 2, 71 | "outputs": [ 72 | { 73 | "output_type": "stream", 74 | "name": "stdout", 75 | "text": [ 76 | "Cloning into 'sd-scripts'...\n", 77 | "remote: Enumerating objects: 4954, done.\u001b[K\n", 78 | "remote: Counting objects: 100% (2460/2460), done.\u001b[K\n", 79 | "remote: Compressing objects: 100% (319/319), done.\u001b[K\n", 80 | "remote: Total 4954 (delta 2285), reused 2202 (delta 2140), pack-reused 2494\u001b[K\n", 81 | "Receiving objects: 100% (4954/4954), 8.58 MiB | 8.67 MiB/s, done.\n", 82 | "Resolving deltas: 100% (3499/3499), done.\n", 83 | "/content/sd-scripts\n" 84 | ] 85 | } 86 | ] 87 | }, 88 | { 89 | "cell_type": "code", 90 | "source": [ 91 | "!pip install -r requirements.txt\n", 92 | "!pip install --upgrade protobuf\n", 93 | "!pip install xformers==0.0.22 triton bitsandbytes" 94 | ], 95 | "metadata": { 96 | "colab": { 97 | "base_uri": "https://localhost:8080/", 98 | "height": 1000 99 | }, 100 | "id": "fMwHk4hAQiPR", 101 | "outputId": "064198a0-3bdf-45bb-b2b0-d457aae279f3" 102 | }, 103 | "execution_count": 3, 104 | "outputs": [ 105 | { 106 | "output_type": "stream", 107 | "name": "stdout", 108 | "text": [ 109 | "Obtaining file:///content/sd-scripts (from -r requirements.txt (line 33))\n", 110 | " Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n", 111 | "Collecting accelerate==0.23.0 (from -r requirements.txt (line 1))\n", 112 | " Downloading accelerate-0.23.0-py3-none-any.whl (258 kB)\n", 113 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m258.1/258.1 kB\u001b[0m \u001b[31m4.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 114 | "\u001b[?25hCollecting transformers==4.30.2 (from -r requirements.txt (line 2))\n", 115 | " Downloading transformers-4.30.2-py3-none-any.whl (7.2 MB)\n", 116 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.2/7.2 MB\u001b[0m \u001b[31m18.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 117 | "\u001b[?25hCollecting diffusers[torch]==0.21.2 (from -r requirements.txt (line 3))\n", 118 | " Downloading diffusers-0.21.2.tar.gz (1.1 MB)\n", 119 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.1/1.1 MB\u001b[0m \u001b[31m34.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 120 | "\u001b[?25h Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n", 121 | " Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n", 122 | " Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", 123 | "Collecting ftfy==6.1.1 (from -r requirements.txt (line 4))\n", 124 | " Downloading ftfy-6.1.1-py3-none-any.whl (53 kB)\n", 125 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m53.1/53.1 kB\u001b[0m \u001b[31m7.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 126 | "\u001b[?25hCollecting opencv-python==4.7.0.68 (from -r requirements.txt (line 6))\n", 127 | " Downloading opencv_python-4.7.0.68-cp37-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (61.8 MB)\n", 128 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m61.8/61.8 MB\u001b[0m \u001b[31m27.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 129 | "\u001b[?25hCollecting einops==0.6.0 (from -r requirements.txt (line 7))\n", 130 | " Downloading einops-0.6.0-py3-none-any.whl (41 kB)\n", 131 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m41.6/41.6 kB\u001b[0m \u001b[31m5.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 132 | "\u001b[?25hCollecting pytorch-lightning==1.9.0 (from -r requirements.txt (line 8))\n", 133 | " Downloading pytorch_lightning-1.9.0-py3-none-any.whl (825 kB)\n", 134 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m825.8/825.8 kB\u001b[0m \u001b[31m71.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 135 | "\u001b[?25hCollecting tensorboard==2.10.1 (from -r requirements.txt (line 10))\n", 136 | " Downloading tensorboard-2.10.1-py3-none-any.whl (5.9 MB)\n", 137 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m5.9/5.9 MB\u001b[0m \u001b[31m108.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 138 | "\u001b[?25hCollecting safetensors==0.3.1 (from -r requirements.txt (line 11))\n", 139 | " Downloading safetensors-0.3.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.3 MB)\n", 140 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.3/1.3 MB\u001b[0m \u001b[31m77.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 141 | "\u001b[?25hRequirement already satisfied: altair==4.2.2 in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 13)) (4.2.2)\n", 142 | "Collecting easygui==0.98.3 (from -r requirements.txt (line 14))\n", 143 | " Downloading easygui-0.98.3-py2.py3-none-any.whl (92 kB)\n", 144 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m92.7/92.7 kB\u001b[0m \u001b[31m13.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 145 | "\u001b[?25hRequirement already satisfied: toml==0.10.2 in /usr/local/lib/python3.10/dist-packages (from -r requirements.txt (line 15)) (0.10.2)\n", 146 | "Collecting voluptuous==0.13.1 (from -r requirements.txt (line 16))\n", 147 | " Downloading voluptuous-0.13.1-py3-none-any.whl (29 kB)\n", 148 | "Collecting huggingface-hub==0.15.1 (from -r requirements.txt (line 17))\n", 149 | " Downloading huggingface_hub-0.15.1-py3-none-any.whl (236 kB)\n", 150 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m236.8/236.8 kB\u001b[0m \u001b[31m29.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 151 | "\u001b[?25hCollecting open-clip-torch==2.20.0 (from -r requirements.txt (line 31))\n", 152 | " Downloading open_clip_torch-2.20.0-py3-none-any.whl (1.5 MB)\n", 153 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.5/1.5 MB\u001b[0m \u001b[31m82.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 154 | "\u001b[?25hRequirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from accelerate==0.23.0->-r requirements.txt (line 1)) (1.23.5)\n", 155 | "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from accelerate==0.23.0->-r requirements.txt (line 1)) (23.2)\n", 156 | "Requirement already satisfied: psutil in /usr/local/lib/python3.10/dist-packages (from accelerate==0.23.0->-r requirements.txt (line 1)) (5.9.5)\n", 157 | "Requirement already satisfied: pyyaml in /usr/local/lib/python3.10/dist-packages (from accelerate==0.23.0->-r requirements.txt (line 1)) (6.0.1)\n", 158 | "Requirement already satisfied: torch>=1.10.0 in /usr/local/lib/python3.10/dist-packages (from accelerate==0.23.0->-r requirements.txt (line 1)) (2.1.0+cu121)\n", 159 | "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from transformers==4.30.2->-r requirements.txt (line 2)) (3.13.1)\n", 160 | "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from transformers==4.30.2->-r requirements.txt (line 2)) (2023.6.3)\n", 161 | "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from transformers==4.30.2->-r requirements.txt (line 2)) (2.31.0)\n", 162 | "Collecting tokenizers!=0.11.3,<0.14,>=0.11.1 (from transformers==4.30.2->-r requirements.txt (line 2))\n", 163 | " Downloading tokenizers-0.13.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.8 MB)\n", 164 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.8/7.8 MB\u001b[0m \u001b[31m107.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 165 | "\u001b[?25hRequirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.10/dist-packages (from transformers==4.30.2->-r requirements.txt (line 2)) (4.66.1)\n", 166 | "Requirement already satisfied: importlib-metadata in /usr/local/lib/python3.10/dist-packages (from diffusers[torch]==0.21.2->-r requirements.txt (line 3)) (7.0.0)\n", 167 | "Requirement already satisfied: Pillow in /usr/local/lib/python3.10/dist-packages (from diffusers[torch]==0.21.2->-r requirements.txt (line 3)) (9.4.0)\n", 168 | "Requirement already satisfied: wcwidth>=0.2.5 in /usr/local/lib/python3.10/dist-packages (from ftfy==6.1.1->-r requirements.txt (line 4)) (0.2.12)\n", 169 | "Requirement already satisfied: fsspec[http]>2021.06.0 in /usr/local/lib/python3.10/dist-packages (from pytorch-lightning==1.9.0->-r requirements.txt (line 8)) (2023.6.0)\n", 170 | "Collecting torchmetrics>=0.7.0 (from pytorch-lightning==1.9.0->-r requirements.txt (line 8))\n", 171 | " Downloading torchmetrics-1.2.1-py3-none-any.whl (806 kB)\n", 172 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m806.1/806.1 kB\u001b[0m \u001b[31m68.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 173 | "\u001b[?25hRequirement already satisfied: typing-extensions>=4.0.0 in /usr/local/lib/python3.10/dist-packages (from pytorch-lightning==1.9.0->-r requirements.txt (line 8)) (4.5.0)\n", 174 | "Collecting lightning-utilities>=0.4.2 (from pytorch-lightning==1.9.0->-r requirements.txt (line 8))\n", 175 | " Downloading lightning_utilities-0.10.0-py3-none-any.whl (24 kB)\n", 176 | "Requirement already satisfied: absl-py>=0.4 in /usr/local/lib/python3.10/dist-packages (from tensorboard==2.10.1->-r requirements.txt (line 10)) (1.4.0)\n", 177 | "Requirement already satisfied: grpcio>=1.24.3 in /usr/local/lib/python3.10/dist-packages (from tensorboard==2.10.1->-r requirements.txt (line 10)) (1.60.0)\n", 178 | "Requirement already satisfied: google-auth<3,>=1.6.3 in /usr/local/lib/python3.10/dist-packages (from tensorboard==2.10.1->-r requirements.txt (line 10)) (2.17.3)\n", 179 | "Collecting google-auth-oauthlib<0.5,>=0.4.1 (from tensorboard==2.10.1->-r requirements.txt (line 10))\n", 180 | " Downloading google_auth_oauthlib-0.4.6-py2.py3-none-any.whl (18 kB)\n", 181 | "Requirement already satisfied: markdown>=2.6.8 in /usr/local/lib/python3.10/dist-packages (from tensorboard==2.10.1->-r requirements.txt (line 10)) (3.5.1)\n", 182 | "Collecting protobuf<3.20,>=3.9.2 (from tensorboard==2.10.1->-r requirements.txt (line 10))\n", 183 | " Downloading protobuf-3.19.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.1 MB)\n", 184 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.1/1.1 MB\u001b[0m \u001b[31m73.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 185 | "\u001b[?25hRequirement already satisfied: setuptools>=41.0.0 in /usr/local/lib/python3.10/dist-packages (from tensorboard==2.10.1->-r requirements.txt (line 10)) (67.7.2)\n", 186 | "Collecting tensorboard-data-server<0.7.0,>=0.6.0 (from tensorboard==2.10.1->-r requirements.txt (line 10))\n", 187 | " Downloading tensorboard_data_server-0.6.1-py3-none-manylinux2010_x86_64.whl (4.9 MB)\n", 188 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m4.9/4.9 MB\u001b[0m \u001b[31m112.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 189 | "\u001b[?25hCollecting tensorboard-plugin-wit>=1.6.0 (from tensorboard==2.10.1->-r requirements.txt (line 10))\n", 190 | " Downloading tensorboard_plugin_wit-1.8.1-py3-none-any.whl (781 kB)\n", 191 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m781.3/781.3 kB\u001b[0m \u001b[31m68.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 192 | "\u001b[?25hRequirement already satisfied: werkzeug>=1.0.1 in /usr/local/lib/python3.10/dist-packages (from tensorboard==2.10.1->-r requirements.txt (line 10)) (3.0.1)\n", 193 | "Requirement already satisfied: wheel>=0.26 in /usr/local/lib/python3.10/dist-packages (from tensorboard==2.10.1->-r requirements.txt (line 10)) (0.42.0)\n", 194 | "Requirement already satisfied: entrypoints in /usr/local/lib/python3.10/dist-packages (from altair==4.2.2->-r requirements.txt (line 13)) (0.4)\n", 195 | "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from altair==4.2.2->-r requirements.txt (line 13)) (3.1.2)\n", 196 | "Requirement already satisfied: jsonschema>=3.0 in /usr/local/lib/python3.10/dist-packages (from altair==4.2.2->-r requirements.txt (line 13)) (4.19.2)\n", 197 | "Requirement already satisfied: pandas>=0.18 in /usr/local/lib/python3.10/dist-packages (from altair==4.2.2->-r requirements.txt (line 13)) (1.5.3)\n", 198 | "Requirement already satisfied: toolz in /usr/local/lib/python3.10/dist-packages (from altair==4.2.2->-r requirements.txt (line 13)) (0.12.0)\n", 199 | "Requirement already satisfied: torchvision in /usr/local/lib/python3.10/dist-packages (from open-clip-torch==2.20.0->-r requirements.txt (line 31)) (0.16.0+cu121)\n", 200 | "Collecting sentencepiece (from open-clip-torch==2.20.0->-r requirements.txt (line 31))\n", 201 | " Downloading sentencepiece-0.1.99-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.3 MB)\n", 202 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.3/1.3 MB\u001b[0m \u001b[31m77.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 203 | "\u001b[?25hCollecting timm (from open-clip-torch==2.20.0->-r requirements.txt (line 31))\n", 204 | " Downloading timm-0.9.12-py3-none-any.whl (2.2 MB)\n", 205 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.2/2.2 MB\u001b[0m \u001b[31m98.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 206 | "\u001b[?25hRequirement already satisfied: aiohttp!=4.0.0a0,!=4.0.0a1 in /usr/local/lib/python3.10/dist-packages (from fsspec[http]>2021.06.0->pytorch-lightning==1.9.0->-r requirements.txt (line 8)) (3.9.1)\n", 207 | "Requirement already satisfied: cachetools<6.0,>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard==2.10.1->-r requirements.txt (line 10)) (5.3.2)\n", 208 | "Requirement already satisfied: pyasn1-modules>=0.2.1 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard==2.10.1->-r requirements.txt (line 10)) (0.3.0)\n", 209 | "Requirement already satisfied: six>=1.9.0 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard==2.10.1->-r requirements.txt (line 10)) (1.16.0)\n", 210 | "Requirement already satisfied: rsa<5,>=3.1.4 in /usr/local/lib/python3.10/dist-packages (from google-auth<3,>=1.6.3->tensorboard==2.10.1->-r requirements.txt (line 10)) (4.9)\n", 211 | "Requirement already satisfied: requests-oauthlib>=0.7.0 in /usr/local/lib/python3.10/dist-packages (from google-auth-oauthlib<0.5,>=0.4.1->tensorboard==2.10.1->-r requirements.txt (line 10)) (1.3.1)\n", 212 | "Requirement already satisfied: attrs>=22.2.0 in /usr/local/lib/python3.10/dist-packages (from jsonschema>=3.0->altair==4.2.2->-r requirements.txt (line 13)) (23.1.0)\n", 213 | "Requirement already satisfied: jsonschema-specifications>=2023.03.6 in /usr/local/lib/python3.10/dist-packages (from jsonschema>=3.0->altair==4.2.2->-r requirements.txt (line 13)) (2023.11.2)\n", 214 | "Requirement already satisfied: referencing>=0.28.4 in /usr/local/lib/python3.10/dist-packages (from jsonschema>=3.0->altair==4.2.2->-r requirements.txt (line 13)) (0.32.0)\n", 215 | "Requirement already satisfied: rpds-py>=0.7.1 in /usr/local/lib/python3.10/dist-packages (from jsonschema>=3.0->altair==4.2.2->-r requirements.txt (line 13)) (0.13.2)\n", 216 | "Requirement already satisfied: python-dateutil>=2.8.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=0.18->altair==4.2.2->-r requirements.txt (line 13)) (2.8.2)\n", 217 | "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas>=0.18->altair==4.2.2->-r requirements.txt (line 13)) (2023.3.post1)\n", 218 | "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->transformers==4.30.2->-r requirements.txt (line 2)) (3.3.2)\n", 219 | "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->transformers==4.30.2->-r requirements.txt (line 2)) (3.6)\n", 220 | "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->transformers==4.30.2->-r requirements.txt (line 2)) (2.0.7)\n", 221 | "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->transformers==4.30.2->-r requirements.txt (line 2)) (2023.11.17)\n", 222 | "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate==0.23.0->-r requirements.txt (line 1)) (1.12)\n", 223 | "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate==0.23.0->-r requirements.txt (line 1)) (3.2.1)\n", 224 | "Requirement already satisfied: triton==2.1.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate==0.23.0->-r requirements.txt (line 1)) (2.1.0)\n", 225 | "Requirement already satisfied: MarkupSafe>=2.1.1 in /usr/local/lib/python3.10/dist-packages (from werkzeug>=1.0.1->tensorboard==2.10.1->-r requirements.txt (line 10)) (2.1.3)\n", 226 | "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.10/dist-packages (from importlib-metadata->diffusers[torch]==0.21.2->-r requirements.txt (line 3)) (3.17.0)\n", 227 | "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]>2021.06.0->pytorch-lightning==1.9.0->-r requirements.txt (line 8)) (6.0.4)\n", 228 | "Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]>2021.06.0->pytorch-lightning==1.9.0->-r requirements.txt (line 8)) (1.9.4)\n", 229 | "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]>2021.06.0->pytorch-lightning==1.9.0->-r requirements.txt (line 8)) (1.4.0)\n", 230 | "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]>2021.06.0->pytorch-lightning==1.9.0->-r requirements.txt (line 8)) (1.3.1)\n", 231 | "Requirement already satisfied: async-timeout<5.0,>=4.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]>2021.06.0->pytorch-lightning==1.9.0->-r requirements.txt (line 8)) (4.0.3)\n", 232 | "Requirement already satisfied: pyasn1<0.6.0,>=0.4.6 in /usr/local/lib/python3.10/dist-packages (from pyasn1-modules>=0.2.1->google-auth<3,>=1.6.3->tensorboard==2.10.1->-r requirements.txt (line 10)) (0.5.1)\n", 233 | "Requirement already satisfied: oauthlib>=3.0.0 in /usr/local/lib/python3.10/dist-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tensorboard==2.10.1->-r requirements.txt (line 10)) (3.2.2)\n", 234 | "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.10.0->accelerate==0.23.0->-r requirements.txt (line 1)) (1.3.0)\n", 235 | "Building wheels for collected packages: diffusers\n", 236 | " Building wheel for diffusers (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", 237 | " Created wheel for diffusers: filename=diffusers-0.21.2-py3-none-any.whl size=1489250 sha256=a914cf1b400f6b9a266ffb8cc28771a1e9e489bce410d241df951e1e81560c4d\n", 238 | " Stored in directory: /root/.cache/pip/wheels/2e/09/32/11c9e42c397d3f3494226b28ba68c4ad4718a68a65dba14ea6\n", 239 | "Successfully built diffusers\n", 240 | "Installing collected packages: voluptuous, tokenizers, tensorboard-plugin-wit, sentencepiece, safetensors, library, easygui, tensorboard-data-server, protobuf, opencv-python, lightning-utilities, ftfy, einops, huggingface-hub, transformers, torchmetrics, google-auth-oauthlib, diffusers, accelerate, timm, tensorboard, pytorch-lightning, open-clip-torch\n", 241 | " Attempting uninstall: tokenizers\n", 242 | " Found existing installation: tokenizers 0.15.0\n", 243 | " Uninstalling tokenizers-0.15.0:\n", 244 | " Successfully uninstalled tokenizers-0.15.0\n", 245 | " Attempting uninstall: safetensors\n", 246 | " Found existing installation: safetensors 0.4.1\n", 247 | " Uninstalling safetensors-0.4.1:\n", 248 | " Successfully uninstalled safetensors-0.4.1\n", 249 | " Running setup.py develop for library\n", 250 | " Attempting uninstall: tensorboard-data-server\n", 251 | " Found existing installation: tensorboard-data-server 0.7.2\n", 252 | " Uninstalling tensorboard-data-server-0.7.2:\n", 253 | " Successfully uninstalled tensorboard-data-server-0.7.2\n", 254 | " Attempting uninstall: protobuf\n", 255 | " Found existing installation: protobuf 3.20.3\n", 256 | " Uninstalling protobuf-3.20.3:\n", 257 | " Successfully uninstalled protobuf-3.20.3\n", 258 | " Attempting uninstall: opencv-python\n", 259 | " Found existing installation: opencv-python 4.8.0.76\n", 260 | " Uninstalling opencv-python-4.8.0.76:\n", 261 | " Successfully uninstalled opencv-python-4.8.0.76\n", 262 | " Attempting uninstall: huggingface-hub\n", 263 | " Found existing installation: huggingface-hub 0.19.4\n", 264 | " Uninstalling huggingface-hub-0.19.4:\n", 265 | " Successfully uninstalled huggingface-hub-0.19.4\n", 266 | " Attempting uninstall: transformers\n", 267 | " Found existing installation: transformers 4.35.2\n", 268 | " Uninstalling transformers-4.35.2:\n", 269 | " Successfully uninstalled transformers-4.35.2\n", 270 | " Attempting uninstall: google-auth-oauthlib\n", 271 | " Found existing installation: google-auth-oauthlib 1.2.0\n", 272 | " Uninstalling google-auth-oauthlib-1.2.0:\n", 273 | " Successfully uninstalled google-auth-oauthlib-1.2.0\n", 274 | " Attempting uninstall: tensorboard\n", 275 | " Found existing installation: tensorboard 2.15.1\n", 276 | " Uninstalling tensorboard-2.15.1:\n", 277 | " Successfully uninstalled tensorboard-2.15.1\n", 278 | "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n", 279 | "pandas-gbq 0.19.2 requires google-auth-oauthlib>=0.7.0, but you have google-auth-oauthlib 0.4.6 which is incompatible.\n", 280 | "tensorflow 2.15.0 requires protobuf!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.20.3, but you have protobuf 3.19.6 which is incompatible.\n", 281 | "tensorflow 2.15.0 requires tensorboard<2.16,>=2.15, but you have tensorboard 2.10.1 which is incompatible.\n", 282 | "tensorflow-datasets 4.9.3 requires protobuf>=3.20, but you have protobuf 3.19.6 which is incompatible.\n", 283 | "tensorflow-metadata 1.14.0 requires protobuf<4.21,>=3.20.3, but you have protobuf 3.19.6 which is incompatible.\u001b[0m\u001b[31m\n", 284 | "\u001b[0mSuccessfully installed accelerate-0.23.0 diffusers-0.21.2 easygui-0.98.3 einops-0.6.0 ftfy-6.1.1 google-auth-oauthlib-0.4.6 huggingface-hub-0.15.1 library-0.0.0 lightning-utilities-0.10.0 open-clip-torch-2.20.0 opencv-python-4.7.0.68 protobuf-3.19.6 pytorch-lightning-1.9.0 safetensors-0.3.1 sentencepiece-0.1.99 tensorboard-2.10.1 tensorboard-data-server-0.6.1 tensorboard-plugin-wit-1.8.1 timm-0.9.12 tokenizers-0.13.3 torchmetrics-1.2.1 transformers-4.30.2 voluptuous-0.13.1\n" 285 | ] 286 | }, 287 | { 288 | "output_type": "display_data", 289 | "data": { 290 | "application/vnd.colab-display-data+json": { 291 | "pip_warning": { 292 | "packages": [ 293 | "google" 294 | ] 295 | } 296 | } 297 | }, 298 | "metadata": {} 299 | }, 300 | { 301 | "output_type": "stream", 302 | "name": "stdout", 303 | "text": [ 304 | "Requirement already satisfied: protobuf in /usr/local/lib/python3.10/dist-packages (3.19.6)\n", 305 | "Collecting protobuf\n", 306 | " Downloading protobuf-4.25.1-cp37-abi3-manylinux2014_x86_64.whl (294 kB)\n", 307 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m294.6/294.6 kB\u001b[0m \u001b[31m4.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 308 | "\u001b[?25hInstalling collected packages: protobuf\n", 309 | " Attempting uninstall: protobuf\n", 310 | " Found existing installation: protobuf 3.19.6\n", 311 | " Uninstalling protobuf-3.19.6:\n", 312 | " Successfully uninstalled protobuf-3.19.6\n", 313 | "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n", 314 | "open-clip-torch 2.20.0 requires protobuf<4, but you have protobuf 4.25.1 which is incompatible.\n", 315 | "pandas-gbq 0.19.2 requires google-auth-oauthlib>=0.7.0, but you have google-auth-oauthlib 0.4.6 which is incompatible.\n", 316 | "tensorboard 2.10.1 requires protobuf<3.20,>=3.9.2, but you have protobuf 4.25.1 which is incompatible.\n", 317 | "tensorflow 2.15.0 requires tensorboard<2.16,>=2.15, but you have tensorboard 2.10.1 which is incompatible.\n", 318 | "tensorflow-metadata 1.14.0 requires protobuf<4.21,>=3.20.3, but you have protobuf 4.25.1 which is incompatible.\u001b[0m\u001b[31m\n", 319 | "\u001b[0mSuccessfully installed protobuf-4.25.1\n", 320 | "Collecting xformers==0.0.22\n", 321 | " Downloading xformers-0.0.22-cp310-cp310-manylinux2014_x86_64.whl (211.6 MB)\n", 322 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m211.6/211.6 MB\u001b[0m \u001b[31m5.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 323 | "\u001b[?25hRequirement already satisfied: triton in /usr/local/lib/python3.10/dist-packages (2.1.0)\n", 324 | "Collecting bitsandbytes\n", 325 | " Downloading bitsandbytes-0.41.3.post2-py3-none-any.whl (92.6 MB)\n", 326 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m92.6/92.6 MB\u001b[0m \u001b[31m18.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 327 | "\u001b[?25hRequirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from xformers==0.0.22) (1.23.5)\n", 328 | "Collecting torch==2.0.1 (from xformers==0.0.22)\n", 329 | " Downloading torch-2.0.1-cp310-cp310-manylinux1_x86_64.whl (619.9 MB)\n", 330 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m619.9/619.9 MB\u001b[0m \u001b[31m2.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 331 | "\u001b[?25hRequirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch==2.0.1->xformers==0.0.22) (3.13.1)\n", 332 | "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.10/dist-packages (from torch==2.0.1->xformers==0.0.22) (4.5.0)\n", 333 | "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch==2.0.1->xformers==0.0.22) (1.12)\n", 334 | "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch==2.0.1->xformers==0.0.22) (3.2.1)\n", 335 | "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch==2.0.1->xformers==0.0.22) (3.1.2)\n", 336 | "Collecting nvidia-cuda-nvrtc-cu11==11.7.99 (from torch==2.0.1->xformers==0.0.22)\n", 337 | " Downloading nvidia_cuda_nvrtc_cu11-11.7.99-2-py3-none-manylinux1_x86_64.whl (21.0 MB)\n", 338 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m21.0/21.0 MB\u001b[0m \u001b[31m66.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 339 | "\u001b[?25hCollecting nvidia-cuda-runtime-cu11==11.7.99 (from torch==2.0.1->xformers==0.0.22)\n", 340 | " Downloading nvidia_cuda_runtime_cu11-11.7.99-py3-none-manylinux1_x86_64.whl (849 kB)\n", 341 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m849.3/849.3 kB\u001b[0m \u001b[31m65.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 342 | "\u001b[?25hCollecting nvidia-cuda-cupti-cu11==11.7.101 (from torch==2.0.1->xformers==0.0.22)\n", 343 | " Downloading nvidia_cuda_cupti_cu11-11.7.101-py3-none-manylinux1_x86_64.whl (11.8 MB)\n", 344 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m11.8/11.8 MB\u001b[0m \u001b[31m100.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 345 | "\u001b[?25hCollecting nvidia-cudnn-cu11==8.5.0.96 (from torch==2.0.1->xformers==0.0.22)\n", 346 | " Downloading nvidia_cudnn_cu11-8.5.0.96-2-py3-none-manylinux1_x86_64.whl (557.1 MB)\n", 347 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m557.1/557.1 MB\u001b[0m \u001b[31m2.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 348 | "\u001b[?25hCollecting nvidia-cublas-cu11==11.10.3.66 (from torch==2.0.1->xformers==0.0.22)\n", 349 | " Downloading nvidia_cublas_cu11-11.10.3.66-py3-none-manylinux1_x86_64.whl (317.1 MB)\n", 350 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m317.1/317.1 MB\u001b[0m \u001b[31m2.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 351 | "\u001b[?25hCollecting nvidia-cufft-cu11==10.9.0.58 (from torch==2.0.1->xformers==0.0.22)\n", 352 | " Downloading nvidia_cufft_cu11-10.9.0.58-py3-none-manylinux1_x86_64.whl (168.4 MB)\n", 353 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m168.4/168.4 MB\u001b[0m \u001b[31m9.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 354 | "\u001b[?25hCollecting nvidia-curand-cu11==10.2.10.91 (from torch==2.0.1->xformers==0.0.22)\n", 355 | " Downloading nvidia_curand_cu11-10.2.10.91-py3-none-manylinux1_x86_64.whl (54.6 MB)\n", 356 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m54.6/54.6 MB\u001b[0m \u001b[31m24.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 357 | "\u001b[?25hCollecting nvidia-cusolver-cu11==11.4.0.1 (from torch==2.0.1->xformers==0.0.22)\n", 358 | " Downloading nvidia_cusolver_cu11-11.4.0.1-2-py3-none-manylinux1_x86_64.whl (102.6 MB)\n", 359 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m102.6/102.6 MB\u001b[0m \u001b[31m16.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 360 | "\u001b[?25hCollecting nvidia-cusparse-cu11==11.7.4.91 (from torch==2.0.1->xformers==0.0.22)\n", 361 | " Downloading nvidia_cusparse_cu11-11.7.4.91-py3-none-manylinux1_x86_64.whl (173.2 MB)\n", 362 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m173.2/173.2 MB\u001b[0m \u001b[31m3.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 363 | "\u001b[?25hCollecting nvidia-nccl-cu11==2.14.3 (from torch==2.0.1->xformers==0.0.22)\n", 364 | " Downloading nvidia_nccl_cu11-2.14.3-py3-none-manylinux1_x86_64.whl (177.1 MB)\n", 365 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m177.1/177.1 MB\u001b[0m \u001b[31m6.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 366 | "\u001b[?25hCollecting nvidia-nvtx-cu11==11.7.91 (from torch==2.0.1->xformers==0.0.22)\n", 367 | " Downloading nvidia_nvtx_cu11-11.7.91-py3-none-manylinux1_x86_64.whl (98 kB)\n", 368 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m98.6/98.6 kB\u001b[0m \u001b[31m14.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 369 | "\u001b[?25hCollecting triton\n", 370 | " Downloading triton-2.0.0-1-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl (63.3 MB)\n", 371 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m63.3/63.3 MB\u001b[0m \u001b[31m25.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 372 | "\u001b[?25hRequirement already satisfied: cmake in /usr/local/lib/python3.10/dist-packages (from triton) (3.27.9)\n", 373 | "Collecting lit (from triton)\n", 374 | " Downloading lit-17.0.6.tar.gz (153 kB)\n", 375 | "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m153.0/153.0 kB\u001b[0m \u001b[31m22.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", 376 | "\u001b[?25h Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n", 377 | " Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n", 378 | " Installing backend dependencies ... \u001b[?25l\u001b[?25hdone\n", 379 | " Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", 380 | "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from nvidia-cublas-cu11==11.10.3.66->torch==2.0.1->xformers==0.0.22) (67.7.2)\n", 381 | "Requirement already satisfied: wheel in /usr/local/lib/python3.10/dist-packages (from nvidia-cublas-cu11==11.10.3.66->torch==2.0.1->xformers==0.0.22) (0.42.0)\n", 382 | "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch==2.0.1->xformers==0.0.22) (2.1.3)\n", 383 | "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch==2.0.1->xformers==0.0.22) (1.3.0)\n", 384 | "Building wheels for collected packages: lit\n", 385 | " Building wheel for lit (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", 386 | " Created wheel for lit: filename=lit-17.0.6-py3-none-any.whl size=93255 sha256=85a129fb69f021984b8156ba660bc8f297bc6205f7e54b8fb604cd281cb8040b\n", 387 | " Stored in directory: /root/.cache/pip/wheels/30/dd/04/47d42976a6a86dc2ab66d7518621ae96f43452c8841d74758a\n", 388 | "Successfully built lit\n", 389 | "Installing collected packages: lit, bitsandbytes, nvidia-nvtx-cu11, nvidia-nccl-cu11, nvidia-cusparse-cu11, nvidia-curand-cu11, nvidia-cufft-cu11, nvidia-cuda-runtime-cu11, nvidia-cuda-nvrtc-cu11, nvidia-cuda-cupti-cu11, nvidia-cublas-cu11, nvidia-cusolver-cu11, nvidia-cudnn-cu11, triton, torch, xformers\n", 390 | " Attempting uninstall: triton\n", 391 | " Found existing installation: triton 2.1.0\n", 392 | " Uninstalling triton-2.1.0:\n", 393 | " Successfully uninstalled triton-2.1.0\n", 394 | " Attempting uninstall: torch\n", 395 | " Found existing installation: torch 2.1.0+cu121\n", 396 | " Uninstalling torch-2.1.0+cu121:\n", 397 | " Successfully uninstalled torch-2.1.0+cu121\n", 398 | "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n", 399 | "open-clip-torch 2.20.0 requires protobuf<4, but you have protobuf 4.25.1 which is incompatible.\n", 400 | "torchaudio 2.1.0+cu121 requires torch==2.1.0, but you have torch 2.0.1 which is incompatible.\n", 401 | "torchdata 0.7.0 requires torch==2.1.0, but you have torch 2.0.1 which is incompatible.\n", 402 | "torchtext 0.16.0 requires torch==2.1.0, but you have torch 2.0.1 which is incompatible.\n", 403 | "torchvision 0.16.0+cu121 requires torch==2.1.0, but you have torch 2.0.1 which is incompatible.\u001b[0m\u001b[31m\n", 404 | "\u001b[0mSuccessfully installed bitsandbytes-0.41.3.post2 lit-17.0.6 nvidia-cublas-cu11-11.10.3.66 nvidia-cuda-cupti-cu11-11.7.101 nvidia-cuda-nvrtc-cu11-11.7.99 nvidia-cuda-runtime-cu11-11.7.99 nvidia-cudnn-cu11-8.5.0.96 nvidia-cufft-cu11-10.9.0.58 nvidia-curand-cu11-10.2.10.91 nvidia-cusolver-cu11-11.4.0.1 nvidia-cusparse-cu11-11.7.4.91 nvidia-nccl-cu11-2.14.3 nvidia-nvtx-cu11-11.7.91 torch-2.0.1 triton-2.0.0 xformers-0.0.22\n" 405 | ] 406 | } 407 | ] 408 | }, 409 | { 410 | "cell_type": "code", 411 | "source": [ 412 | "%env PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION python" 413 | ], 414 | "metadata": { 415 | "colab": { 416 | "base_uri": "https://localhost:8080/" 417 | }, 418 | "id": "BhrDr3YqQlhL", 419 | "outputId": "5b883b41-8888-41a4-9155-ece8138819e0" 420 | }, 421 | "execution_count": 3, 422 | "outputs": [ 423 | { 424 | "output_type": "stream", 425 | "name": "stdout", 426 | "text": [ 427 | "env: PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python\n" 428 | ] 429 | } 430 | ] 431 | }, 432 | { 433 | "cell_type": "code", 434 | "source": [ 435 | "# https://note.com/kohya_ss/n/nb20c5187e15a" 436 | ], 437 | "metadata": { 438 | "id": "w9Uc7loHRAwC" 439 | }, 440 | "execution_count": 5, 441 | "outputs": [] 442 | }, 443 | { 444 | "cell_type": "code", 445 | "source": [ 446 | "dataset = \"\"\"[general]\n", 447 | "enable_bucket = true\n", 448 | "\n", 449 | "[[datasets]]\n", 450 | "resolution = 512\n", 451 | "batch_size = 4\n", 452 | "\n", 453 | "[[datasets.subsets]]\n", 454 | "image_dir = '/content/drive/MyDrive/AI/DB/lora_train_sample_pack/train/20_usu frog'\n", 455 | "class_tokens = 'shs frog'\n", 456 | "num_repeats = 10\n", 457 | "\n", 458 | " [[datasets.subsets]]\n", 459 | "is_reg = true\n", 460 | "image_dir = '/content/drive/MyDrive/AI/DB/lora_train_sample_pack/reg/1_frog'\n", 461 | "class_tokens = 'frog'\n", 462 | "num_repeats = 1\n", 463 | "\"\"\"\n", 464 | "\n", 465 | "with open(\"dataset.toml\", \"w\") as f:\n", 466 | " f.write(dataset)" 467 | ], 468 | "metadata": { 469 | "id": "iqWiTXShQrB2" 470 | }, 471 | "execution_count": 10, 472 | "outputs": [] 473 | }, 474 | { 475 | "cell_type": "code", 476 | "source": [ 477 | "!accelerate launch --num_cpu_threads_per_process 1 train_db.py \\\n", 478 | " --pretrained_model_name_or_path=\"stabilityai/stable-diffusion-2-1-base\" \\\n", 479 | " --dataset_config=\"dataset.toml\" \\\n", 480 | " --output_dir=\"/content/drive/MyDrive/AI/DB/Model/frog\" \\\n", 481 | " --output_name=\"frog\" \\\n", 482 | " --save_model_as=safetensors \\\n", 483 | " --prior_loss_weight=1.0 \\\n", 484 | " --max_train_steps=1600 \\\n", 485 | " --learning_rate=1e-6 \\\n", 486 | " --optimizer_type=\"AdamW8bit\" \\\n", 487 | " --xformers \\\n", 488 | " --mixed_precision=\"fp16\" \\\n", 489 | " --cache_latents \\\n", 490 | " --gradient_checkpointing \\\n", 491 | " --v2" 492 | ], 493 | "metadata": { 494 | "colab": { 495 | "base_uri": "https://localhost:8080/" 496 | }, 497 | "id": "4LggEndhSLel", 498 | "outputId": "e51655bf-08f7-4ea6-942b-818feaf53095" 499 | }, 500 | "execution_count": 12, 501 | "outputs": [ 502 | { 503 | "output_type": "stream", 504 | "name": "stdout", 505 | "text": [ 506 | "/usr/local/lib/python3.10/dist-packages/torchvision/io/image.py:13: UserWarning: Failed to load image Python extension: '/usr/local/lib/python3.10/dist-packages/torchvision/image.so: undefined symbol: _ZN3c104cuda9SetDeviceEi'If you don't plan on using image functionality from `torchvision.io`, you can ignore this warning. Otherwise, there might be something wrong with your environment. Did you have `libjpeg` or `libpng` installed before building `torchvision` from source?\n", 507 | " warn(\n", 508 | "The following values were not passed to `accelerate launch` and had defaults used instead:\n", 509 | "\t`--num_processes` was set to a value of `1`\n", 510 | "\t`--num_machines` was set to a value of `1`\n", 511 | "\t`--mixed_precision` was set to a value of `'no'`\n", 512 | "\t`--dynamo_backend` was set to a value of `'no'`\n", 513 | "To avoid this warning pass in values for each of the problematic parameters or run `accelerate config`.\n", 514 | "/usr/local/lib/python3.10/dist-packages/torchvision/io/image.py:13: UserWarning: Failed to load image Python extension: '/usr/local/lib/python3.10/dist-packages/torchvision/image.so: undefined symbol: _ZN3c104cuda9SetDeviceEi'If you don't plan on using image functionality from `torchvision.io`, you can ignore this warning. Otherwise, there might be something wrong with your environment. Did you have `libjpeg` or `libpng` installed before building `torchvision` from source?\n", 515 | " warn(\n", 516 | "2023-12-18 09:48:47.597548: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", 517 | "2023-12-18 09:48:47.597599: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", 518 | "2023-12-18 09:48:47.598958: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n", 519 | "2023-12-18 09:48:48.874111: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n", 520 | "prepare tokenizer\n", 521 | "Load dataset config from dataset.toml\n", 522 | "prepare images.\n", 523 | "found directory /content/drive/MyDrive/AI/DB/lora_train_sample_pack/train/20_usu frog contains 15 image files\n", 524 | "No caption file found for 15 images. Training will continue without captions for these images. If class token exists, it will be used. / 15枚の画像にキャプションファイルが見つかりませんでした。これらの画像についてはキャプションなしで学習を続行します。class tokenが存在する場合はそれを使います。\n", 525 | "/content/drive/MyDrive/AI/DB/lora_train_sample_pack/train/20_usu frog/[_c_]chojuganso0001_s1024_chojuganso0001_0.png\n", 526 | "/content/drive/MyDrive/AI/DB/lora_train_sample_pack/train/20_usu frog/_c_choju2_0011_s1024_choju2_0011_6.png\n", 527 | "/content/drive/MyDrive/AI/DB/lora_train_sample_pack/train/20_usu frog/_c_chojuganso0002_s1024_chojuganso0002_0.png\n", 528 | "/content/drive/MyDrive/AI/DB/lora_train_sample_pack/train/20_usu frog/_c_chojuganso0003_s1024_chojuganso0003_0.png\n", 529 | "/content/drive/MyDrive/AI/DB/lora_train_sample_pack/train/20_usu frog/_c_chojuganso0005_s1024_chojuganso0005_0.png\n", 530 | "/content/drive/MyDrive/AI/DB/lora_train_sample_pack/train/20_usu frog/_c_chojuganso0009_s1024_chojuganso0009_0.png... and 10 more\n", 531 | "found directory /content/drive/MyDrive/AI/DB/lora_train_sample_pack/reg/1_frog contains 50 image files\n", 532 | "No caption file found for 50 images. Training will continue without captions for these images. If class token exists, it will be used. / 50枚の画像にキャプションファイルが見つかりませんでした。これらの画像についてはキャプションなしで学習を続行します。class tokenが存在する場合はそれを使います。\n", 533 | "/content/drive/MyDrive/AI/DB/lora_train_sample_pack/reg/1_frog/im_20220926233500_0.png\n", 534 | "/content/drive/MyDrive/AI/DB/lora_train_sample_pack/reg/1_frog/im_20220926233500_1.png\n", 535 | "/content/drive/MyDrive/AI/DB/lora_train_sample_pack/reg/1_frog/im_20220926233500_2.png\n", 536 | "/content/drive/MyDrive/AI/DB/lora_train_sample_pack/reg/1_frog/im_20220926233500_3.png\n", 537 | "/content/drive/MyDrive/AI/DB/lora_train_sample_pack/reg/1_frog/im_20220926233511_0.png\n", 538 | "/content/drive/MyDrive/AI/DB/lora_train_sample_pack/reg/1_frog/im_20220926233511_1.png... and 45 more\n", 539 | "150 train images with repeating.\n", 540 | "50 reg images.\n", 541 | "[Dataset 0]\n", 542 | " batch_size: 4\n", 543 | " resolution: (512, 512)\n", 544 | " enable_bucket: True\n", 545 | " min_bucket_reso: 256\n", 546 | " max_bucket_reso: 1024\n", 547 | " bucket_reso_steps: 64\n", 548 | " bucket_no_upscale: False\n", 549 | "\n", 550 | " [Subset 0 of Dataset 0]\n", 551 | " image_dir: \"/content/drive/MyDrive/AI/DB/lora_train_sample_pack/train/20_usu frog\"\n", 552 | " image_count: 15\n", 553 | " num_repeats: 10\n", 554 | " shuffle_caption: False\n", 555 | " keep_tokens: 0\n", 556 | " caption_dropout_rate: 0.0\n", 557 | " caption_dropout_every_n_epoches: 0\n", 558 | " caption_tag_dropout_rate: 0.0\n", 559 | " caption_prefix: None\n", 560 | " caption_suffix: None\n", 561 | " color_aug: False\n", 562 | " flip_aug: False\n", 563 | " face_crop_aug_range: None\n", 564 | " random_crop: False\n", 565 | " token_warmup_min: 1,\n", 566 | " token_warmup_step: 0,\n", 567 | " is_reg: False\n", 568 | " class_tokens: shs frog\n", 569 | " caption_extension: .caption\n", 570 | "\n", 571 | " [Subset 1 of Dataset 0]\n", 572 | " image_dir: \"/content/drive/MyDrive/AI/DB/lora_train_sample_pack/reg/1_frog\"\n", 573 | " image_count: 50\n", 574 | " num_repeats: 1\n", 575 | " shuffle_caption: False\n", 576 | " keep_tokens: 0\n", 577 | " caption_dropout_rate: 0.0\n", 578 | " caption_dropout_every_n_epoches: 0\n", 579 | " caption_tag_dropout_rate: 0.0\n", 580 | " caption_prefix: None\n", 581 | " caption_suffix: None\n", 582 | " color_aug: False\n", 583 | " flip_aug: False\n", 584 | " face_crop_aug_range: None\n", 585 | " random_crop: False\n", 586 | " token_warmup_min: 1,\n", 587 | " token_warmup_step: 0,\n", 588 | " is_reg: True\n", 589 | " class_tokens: frog\n", 590 | " caption_extension: .caption\n", 591 | "\n", 592 | "\n", 593 | "[Dataset 0]\n", 594 | "loading image sizes.\n", 595 | "100% 65/65 [00:00<00:00, 926.17it/s]\n", 596 | "make buckets\n", 597 | "number of images (including repeats) / 各bucketの画像枚数（繰り返し回数を含む）\n", 598 | "bucket 0: resolution (512, 512), count: 300\n", 599 | "mean ar error (without repeats): 0.0\n", 600 | "prepare accelerator\n", 601 | "loading model for process 0/1\n", 602 | "load Diffusers pretrained models: stabilityai/stable-diffusion-2-1-base\n", 603 | "Loading pipeline components...: 100% 5/5 [00:00<00:00, 5.30it/s]\n", 604 | "UNet2DConditionModel: 64, [5, 10, 20, 20], 1024, True, False\n", 605 | "U-Net converted to original U-Net\n", 606 | "Enable xformers for U-Net\n", 607 | "[Dataset 0]\n", 608 | "caching latents.\n", 609 | "checking cache validity...\n", 610 | "100% 65/65 [00:00<00:00, 721242.75it/s]\n", 611 | "caching latents...\n", 612 | "100% 65/65 [00:08<00:00, 7.56it/s]\n", 613 | "CrossAttnDownBlock2D False -> True\n", 614 | "CrossAttnDownBlock2D False -> True\n", 615 | "CrossAttnDownBlock2D False -> True\n", 616 | "DownBlock2D False -> True\n", 617 | "UNetMidBlock2DCrossAttn False -> True\n", 618 | "UpBlock2D False -> True\n", 619 | "CrossAttnUpBlock2D False -> True\n", 620 | "CrossAttnUpBlock2D False -> True\n", 621 | "CrossAttnUpBlock2D False -> True\n", 622 | "prepare optimizer, data loader etc.\n", 623 | "use 8-bit AdamW optimizer | {}\n", 624 | "running training / 学習開始\n", 625 | " num train images * repeats / 学習画像の数×繰り返し回数: 150\n", 626 | " num reg images / 正則化画像の数: 50\n", 627 | " num batches per epoch / 1epochのバッチ数: 75\n", 628 | " num epochs / epoch数: 22\n", 629 | " batch size per device / バッチサイズ: 1\n", 630 | " total train batch size (with parallel & distributed & accumulation) / 総バッチサイズ（並列学習、勾配合計含む）: 1\n", 631 | " gradient ccumulation steps / 勾配を合計するステップ数 = 1\n", 632 | " total optimization steps / 学習ステップ数: 1600\n", 633 | "steps: 0% 0/1600 [00:00