├── LLaVA_1.5 ├── .gitignore ├── LICENSE ├── README.md ├── docs │ ├── Customize_Component.md │ ├── Data.md │ ├── Evaluation.md │ ├── Finetune_Custom_Data.md │ ├── LLaVA_Bench.md │ ├── LLaVA_from_LLaMA2.md │ ├── LoRA.md │ ├── MODEL_ZOO.md │ ├── ScienceQA.md │ └── Windows.md ├── images │ ├── demo_cli.gif │ ├── llava_example_cmp.png │ ├── llava_logo.png │ └── llava_v1_5_radar.jpg ├── llava │ ├── __init__.py │ ├── constants.py │ ├── conversation.py │ ├── eval │ │ ├── eval_gpt_review.py │ │ ├── eval_gpt_review_bench.py │ │ ├── eval_gpt_review_visual.py │ │ ├── eval_pope.py │ │ ├── eval_science_qa.py │ │ ├── eval_science_qa_gpt4.py │ │ ├── eval_science_qa_gpt4_requery.py │ │ ├── eval_textvqa.py │ │ ├── generate_webpage_data_from_table.py │ │ ├── m4c_evaluator.py │ │ ├── model_qa.py │ │ ├── model_vqa.py │ │ ├── model_vqa_loader.py │ │ ├── model_vqa_mmbench.py │ │ ├── model_vqa_science.py │ │ ├── qa_baseline_gpt35.py │ │ ├── run_llava.py │ │ ├── statistical_analysis.py │ │ ├── summarize_gpt_review.py │ │ └── webpage │ │ │ ├── figures │ │ │ ├── alpaca.png │ │ │ ├── bard.jpg │ │ │ ├── chatgpt.svg │ │ │ ├── llama.jpg │ │ │ ├── swords_FILL0_wght300_GRAD0_opsz48.svg │ │ │ └── vicuna.jpeg │ │ │ ├── index.html │ │ │ ├── script.js │ │ │ └── styles.css │ ├── mm_utils.py │ ├── model │ │ ├── __init__.py │ │ ├── apply_delta.py │ │ ├── builder.py │ │ ├── consolidate.py │ │ ├── language_model │ │ │ ├── llava_llama.py │ │ │ ├── llava_mpt.py │ │ │ ├── modeling_llama.py │ │ │ └── mpt │ │ │ │ ├── adapt_tokenizer.py │ │ │ │ ├── attention.py │ │ │ │ ├── blocks.py │ │ │ │ ├── configuration_mpt.py │ │ │ │ ├── custom_embedding.py │ │ │ │ ├── flash_attn_triton.py │ │ │ │ ├── hf_prefixlm_converter.py │ │ │ │ ├── meta_init_context.py │ │ │ │ ├── modeling_mpt.py │ │ │ │ ├── norm.py │ │ │ │ └── param_init_fns.py │ │ ├── llava_arch.py │ │ ├── make_delta.py │ │ ├── multimodal_encoder │ │ │ ├── builder.py │ │ │ └── clip_encoder.py │ │ ├── multimodal_projector │ │ │ └── builder.py │ │ └── utils.py │ ├── serve │ │ ├── __init__.py │ │ ├── cli.py │ │ ├── controller.py │ │ ├── examples │ │ │ ├── extreme_ironing.jpg │ │ │ └── waterview.jpg │ │ ├── gradio_web_server.py │ │ ├── model_worker.py │ │ ├── register_worker.py │ │ └── test_message.py │ ├── train │ │ ├── llama_flash_attn_monkey_patch.py │ │ ├── llava_trainer.py │ │ ├── train.py │ │ └── train_mem.py │ └── utils.py ├── playground │ └── data │ │ └── prompts │ │ ├── complex_reasoning │ │ ├── 000_caps.txt │ │ ├── 000_conv.txt │ │ ├── 001_caps.txt │ │ ├── 001_conv.txt │ │ ├── 002_caps.txt │ │ ├── 002_conv.txt │ │ └── system_message.txt │ │ ├── conversation │ │ ├── 000_caps.txt │ │ ├── 000_conv.txt │ │ ├── 001_caps.txt │ │ ├── 001_conv.txt │ │ └── system_message.txt │ │ └── detail_description │ │ ├── 000_caps.txt │ │ ├── 000_conv.txt │ │ ├── 001_caps.txt │ │ ├── 001_conv.txt │ │ ├── 002_caps.txt │ │ ├── 002_conv.txt │ │ └── system_message.txt ├── pyproject.toml └── scripts │ ├── convert_gqa_for_eval.py │ ├── convert_mmbench_for_submission.py │ ├── convert_mmvet_for_eval.py │ ├── convert_seed_for_submission.py │ ├── convert_sqa_to_llava.py │ ├── convert_sqa_to_llava_base_prompt.py │ ├── convert_vizwiz_for_submission.py │ ├── convert_vqav2_for_submission.py │ ├── extract_mm_projector.py │ ├── finetune.sh │ ├── finetune_full_schedule.sh │ ├── finetune_lora.sh │ ├── finetune_qlora.sh │ ├── finetune_sqa.sh │ ├── merge_lora_weights.py │ ├── pretrain.sh │ ├── sqa_eval_batch.sh │ ├── sqa_eval_gather.sh │ └── v1_5 │ ├── eval │ ├── gqa.sh │ ├── llavabench.sh │ ├── mmbench.sh │ ├── mmbench_cn.sh │ ├── mme.sh │ ├── mmvet.sh │ ├── pope.sh │ ├── seed.sh │ ├── sqa.sh │ ├── textvqa.sh │ ├── vizwiz.sh │ └── vqav2.sh │ ├── finetune.sh │ ├── finetune_lora.sh │ ├── finetune_task.sh │ ├── finetune_task_lora.sh │ └── pretrain.sh ├── LLaVA_HR ├── .gitattributes ├── .gitignore ├── Evaluation.md ├── LICENSE ├── README.md ├── assets │ ├── example.jpg │ ├── fig1.png │ └── logo.png ├── llava_hr │ ├── __init__.py │ ├── constants.py │ ├── conversation.py │ ├── eval │ │ ├── build_query.py │ │ ├── calculate_score.py │ │ ├── eval_caption.py │ │ ├── eval_gpt_review.py │ │ ├── eval_gpt_review_bench.py │ │ ├── eval_gpt_review_visual.py │ │ ├── eval_mmmu_only.py │ │ ├── eval_ocrvqa.py │ │ ├── eval_okvqa.py │ │ ├── eval_pope.py │ │ ├── eval_rec.py │ │ ├── eval_science_qa.py │ │ ├── eval_science_qa_gpt4.py │ │ ├── eval_science_qa_gpt4_requery.py │ │ ├── eval_textvqa.py │ │ ├── extract_answer.py │ │ ├── generate_webpage_data_from_table.py │ │ ├── m4c_evaluator.py │ │ ├── mmmu_utils │ │ │ ├── data_utils.py │ │ │ ├── eval_utils.py │ │ │ └── model_utils.py │ │ ├── model_caption_loader.py │ │ ├── model_mathvista.py │ │ ├── model_mmmu.py │ │ ├── model_qa.py │ │ ├── model_rec_loader.py │ │ ├── model_speed.py │ │ ├── model_vqa.py │ │ ├── model_vqa_loader.py │ │ ├── model_vqa_loader_mme.py │ │ ├── model_vqa_mmbench.py │ │ ├── model_vqa_science.py │ │ ├── model_vqa_torchstone.py │ │ ├── parse_and_eval_mmmu.py │ │ ├── print_mmmu_results.py │ │ ├── prompts │ │ │ └── ext_ans.py │ │ ├── qa_baseline_gpt35.py │ │ ├── run_llava.py │ │ ├── summarize_gpt_review.py │ │ ├── utilities.py │ │ ├── vqa.py │ │ ├── vqa_eval.py │ │ └── webpage │ │ │ ├── figures │ │ │ ├── alpaca.png │ │ │ ├── bard.jpg │ │ │ ├── chatgpt.svg │ │ │ ├── llama.jpg │ │ │ ├── swords_FILL0_wght300_GRAD0_opsz48.svg │ │ │ └── vicuna.jpeg │ │ │ ├── index.html │ │ │ ├── script.js │ │ │ └── styles.css │ ├── mm_utils.py │ ├── model │ │ ├── __init__.py │ │ ├── apply_delta.py │ │ ├── apply_lavin.py │ │ ├── builder.py │ │ ├── consolidate.py │ │ ├── language_model │ │ │ ├── llava_llama.py │ │ │ ├── llava_mpt.py │ │ │ ├── modeling_llama.py │ │ │ └── mpt │ │ │ │ ├── adapt_tokenizer.py │ │ │ │ ├── attention.py │ │ │ │ ├── blocks.py │ │ │ │ ├── configuration_mpt.py │ │ │ │ ├── custom_embedding.py │ │ │ │ ├── flash_attn_triton.py │ │ │ │ ├── hf_prefixlm_converter.py │ │ │ │ ├── meta_init_context.py │ │ │ │ ├── modeling_mpt.py │ │ │ │ ├── norm.py │ │ │ │ └── param_init_fns.py │ │ ├── llava_arch.py │ │ ├── make_delta.py │ │ ├── multimodal_encoder │ │ │ ├── apply_repadapter.py │ │ │ ├── builder.py │ │ │ ├── clip_encoder.py │ │ │ ├── convnext.py │ │ │ ├── convnext_encoder.py │ │ │ ├── eva_clip_encoder.py │ │ │ └── multipath_encoder_wapper.py │ │ ├── multimodal_projector │ │ │ └── builder.py │ │ └── utils.py │ ├── serve │ │ ├── __init__.py │ │ ├── cli.py │ │ ├── controller.py │ │ ├── examples │ │ │ ├── extreme_ironing.jpg │ │ │ └── waterview.jpg │ │ ├── gradio_web_server.py │ │ ├── model_worker.py │ │ ├── register_worker.py │ │ └── test_message.py │ ├── test │ │ ├── dataload.py │ │ ├── dataset.py │ │ ├── model_vqa_science.py │ │ └── run.sh │ ├── train │ │ ├── llama_flash_attn_monkey_patch.py │ │ ├── llava_trainer.py │ │ ├── train.py │ │ └── train_mem.py │ └── utils.py ├── playground │ └── data │ │ └── prompts │ │ ├── complex_reasoning │ │ ├── 000_caps.txt │ │ ├── 000_conv.txt │ │ ├── 001_caps.txt │ │ ├── 001_conv.txt │ │ ├── 002_caps.txt │ │ ├── 002_conv.txt │ │ └── system_message.txt │ │ ├── conversation │ │ ├── 000_caps.txt │ │ ├── 000_conv.txt │ │ ├── 001_caps.txt │ │ ├── 001_conv.txt │ │ └── system_message.txt │ │ └── detail_description │ │ ├── 000_caps.txt │ │ ├── 000_conv.txt │ │ ├── 001_caps.txt │ │ ├── 001_conv.txt │ │ ├── 002_caps.txt │ │ ├── 002_conv.txt │ │ └── system_message.txt ├── pyproject.toml └── scripts │ ├── convert_gqa_for_eval.py │ ├── convert_mmbench_for_submission.py │ ├── convert_mmvet_for_eval.py │ ├── convert_seed_for_submission.py │ ├── convert_sqa_to_llava.py │ ├── convert_sqa_to_llava_base_prompt.py │ ├── convert_torchstone_for_submission.py │ ├── convert_vizwiz_for_submission.py │ ├── convert_vqav2_for_submission.py │ ├── finetune.sh │ ├── finetune_full_schedule.sh │ ├── finetune_lora.sh │ ├── finetune_qlora.sh │ ├── finetune_sqa.sh │ ├── merge_lora_weights.py │ ├── pretrain.sh │ ├── pretrain_llama2.sh │ ├── sqa_eval_batch.sh │ ├── sqa_eval_gather.sh │ └── v1_5 │ ├── eval.sh │ ├── eval │ ├── gqa.sh │ ├── llavabench.sh │ ├── mmbench.sh │ ├── mmbench_cn.sh │ ├── mme.sh │ ├── mmvet.sh │ ├── my_pretrain_lavin.sh │ ├── pope.sh │ ├── seed.sh │ ├── sqa.sh │ ├── textvqa.sh │ ├── vizwiz.sh │ └── vqav2.sh │ ├── eval_all_vqa.sh │ ├── eval_full │ ├── coco_caption.sh │ ├── gqa.sh │ ├── llavabench.sh │ ├── mathvista.sh │ ├── mmbench.sh │ ├── mmbench_cn.sh │ ├── mme.sh │ ├── mmmu.sh │ ├── mmvet.sh │ ├── ocrvqa.sh │ ├── okvqa.sh │ ├── pope.sh │ ├── rec.sh │ ├── seed.sh │ ├── sqa.sh │ ├── textvqa.sh │ ├── torchstone.sh │ ├── vizwiz.sh │ └── vqav2.sh │ ├── eval_ocrqa.sh │ ├── pretrain_llava_hr.sh │ ├── train_eval_llava.sh │ ├── train_eval_llava_exr_multi_nodes_stage1.sh │ ├── train_eval_llava_exr_multi_nodes_stage2.sh │ ├── train_eval_llava_hr.sh │ └── train_eval_llava_hr_x.sh ├── LLaVA_NEXT ├── .devcontainer │ ├── Dockerfile │ ├── devcontainer.env │ ├── devcontainer.json │ └── postCreateCommand.sh ├── .dockerignore ├── .editorconfig ├── .gitattributes ├── .gitignore ├── LICENSE ├── README.md ├── cog.yaml ├── docs │ ├── Customize_Component.md │ ├── Data.md │ ├── Evaluation.md │ ├── Finetune_Custom_Data.md │ ├── Intel.md │ ├── LLaVA_Bench.md │ ├── LLaVA_from_LLaMA2.md │ ├── LoRA.md │ ├── MODEL_ZOO.md │ ├── ScienceQA.md │ ├── Windows.md │ └── macOS.md ├── images │ ├── demo_cli.gif │ ├── llava_example_cmp.png │ ├── llava_logo.png │ └── llava_v1_5_radar.jpg ├── llava │ ├── __init__.py │ ├── constants.py │ ├── conversation.py │ ├── eval │ │ ├── eval_gpt_review.py │ │ ├── eval_gpt_review_bench.py │ │ ├── eval_gpt_review_visual.py │ │ ├── eval_pope.py │ │ ├── eval_science_qa.py │ │ ├── eval_science_qa_gpt4.py │ │ ├── eval_science_qa_gpt4_requery.py │ │ ├── eval_textvqa.py │ │ ├── fitprune_llavanext.py │ │ ├── generate_webpage_data_from_table.py │ │ ├── m4c_evaluator.py │ │ ├── model_qa.py │ │ ├── model_vqa.py │ │ ├── model_vqa_loader.py │ │ ├── model_vqa_mmbench.py │ │ ├── model_vqa_science.py │ │ ├── qa_baseline_gpt35.py │ │ ├── run_llava.py │ │ ├── summarize_gpt_review.py │ │ └── webpage │ │ │ ├── figures │ │ │ ├── alpaca.png │ │ │ ├── bard.jpg │ │ │ ├── chatgpt.svg │ │ │ ├── llama.jpg │ │ │ ├── swords_FILL0_wght300_GRAD0_opsz48.svg │ │ │ └── vicuna.jpeg │ │ │ ├── index.html │ │ │ ├── script.js │ │ │ └── styles.css │ ├── mm_utils.py │ ├── model │ │ ├── __init__.py │ │ ├── apply_delta.py │ │ ├── builder.py │ │ ├── consolidate.py │ │ ├── language_model │ │ │ ├── llava_llama.py │ │ │ ├── llava_mistral.py │ │ │ ├── llava_mpt.py │ │ │ └── modeling_llama.py │ │ ├── llava_arch.py │ │ ├── make_delta.py │ │ ├── multimodal_encoder │ │ │ ├── builder.py │ │ │ └── clip_encoder.py │ │ ├── multimodal_projector │ │ │ └── builder.py │ │ └── utils.py │ ├── serve │ │ ├── __init__.py │ │ ├── cli.py │ │ ├── controller.py │ │ ├── examples │ │ │ ├── extreme_ironing.jpg │ │ │ └── waterview.jpg │ │ ├── gradio_web_server.py │ │ ├── model_worker.py │ │ ├── register_worker.py │ │ ├── sglang_worker.py │ │ └── test_message.py │ ├── train │ │ ├── llama_flash_attn_monkey_patch.py │ │ ├── llama_xformers_attn_monkey_patch.py │ │ ├── llava_trainer.py │ │ ├── train.py │ │ ├── train_mem.py │ │ └── train_xformers.py │ └── utils.py ├── playground │ └── data │ │ └── prompts │ │ ├── complex_reasoning │ │ ├── 000_caps.txt │ │ ├── 000_conv.txt │ │ ├── 001_caps.txt │ │ ├── 001_conv.txt │ │ ├── 002_caps.txt │ │ ├── 002_conv.txt │ │ └── system_message.txt │ │ ├── conversation │ │ ├── 000_caps.txt │ │ ├── 000_conv.txt │ │ ├── 001_caps.txt │ │ ├── 001_conv.txt │ │ └── system_message.txt │ │ └── detail_description │ │ ├── 000_caps.txt │ │ ├── 000_conv.txt │ │ ├── 001_caps.txt │ │ ├── 001_conv.txt │ │ ├── 002_caps.txt │ │ ├── 002_conv.txt │ │ └── system_message.txt ├── predict.py ├── pyproject.toml └── scripts │ ├── convert_gqa_for_eval.py │ ├── convert_mmbench_for_submission.py │ ├── convert_mmvet_for_eval.py │ ├── convert_seed_for_submission.py │ ├── convert_sqa_to_llava.py │ ├── convert_sqa_to_llava_base_prompt.py │ ├── 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