├── .gitattributes ├── .gitignore ├── LICENSE ├── README.md ├── cog.yaml ├── docs ├── Customize_Component.md ├── Data.md ├── Evaluation.md ├── Finetune_Custom_Data.md ├── ScienceQA.md ├── table1.png └── teaser_figure.png ├── 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_loader_text_only.py │ ├── model_vqa_mmbench.py │ ├── model_vqa_mmbench_text_only.py │ ├── model_vqa_qbench.py │ ├── model_vqa_science.py │ ├── model_vqa_science_text_only.py │ ├── model_vqa_text_only.py │ ├── qa_baseline_gpt35.py │ ├── run_llava.py │ ├── summarize_gpt_review.py │ ├── table │ │ ├── answer │ │ │ ├── answer_alpaca-13b.jsonl │ │ │ ├── answer_bard.jsonl │ │ │ ├── answer_gpt35.jsonl │ │ │ ├── answer_llama-13b.jsonl │ │ │ └── answer_vicuna-13b.jsonl │ │ ├── caps_boxes_coco2014_val_80.jsonl │ │ ├── model.jsonl │ │ ├── prompt.jsonl │ │ ├── question.jsonl │ │ ├── results │ │ │ ├── test_sqa_llava_13b_v0.json │ │ │ └── test_sqa_llava_lcs_558k_sqa_12e_vicuna_v1_3_13b.json │ │ ├── review │ │ │ ├── review_alpaca-13b_vicuna-13b.jsonl │ │ │ ├── review_bard_vicuna-13b.jsonl │ │ │ ├── review_gpt35_vicuna-13b.jsonl │ │ │ └── review_llama-13b_vicuna-13b.jsonl │ │ ├── reviewer.jsonl │ │ └── rule.json │ └── 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 │ │ └── 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 │ ├── llama_xformers_attn_monkey_patch.py │ ├── llava_trainer.py │ ├── train.py │ ├── train_mem.py │ └── train_xformers.py └── utils.py ├── playground └── data_VT │ └── README.md ├── preprocess ├── collect_gpt4v_VT │ ├── coco_imageID_61k.txt │ ├── coco_preprocess.py │ ├── gpt4v.py │ ├── gqa_imageID.txt │ ├── mm-vet_imageID.txt │ ├── mmmu_image_ids.txt │ └── mmvp_image_ids.txt ├── gpt_eval │ ├── gpt_eval_mmvp.py │ └── gpt_eval_vqa.py ├── merge_with_VT │ ├── merge_eval_dataset_with_VT.py │ └── merge_scienceqa_with_VT.py └── mmbench │ └── convert_mmbench_images.py ├── pyproject.toml └── scripts ├── LLaVA-VT ├── eval │ ├── eval_multi_datasets_with_VT.sh │ ├── gqa │ │ └── gqa.sh │ ├── llavabench │ │ └── llavabench.sh │ ├── mmbench │ │ └── mmbench.sh │ ├── mmmu │ │ └── mmmu.sh │ ├── mmvet │ │ └── mmvet.sh │ ├── mmvp_mc │ │ ├── eval_mmvp_mc_acc.py │ │ └── mmvp_mc.sh │ ├── pope │ │ └── pope.sh │ ├── scienceqa │ │ └── scienceqa.sh │ ├── textvqa │ │ └── textvqa.sh │ ├── vizwiz │ │ └── vizwiz.sh │ └── vqav2 │ │ └── vqav2_dev.sh └── train │ └── finetune_LLaVA-VT-13B.sh ├── VTGenerator ├── infer │ ├── eval_images_gen_vt.sh │ ├── train_images_gen_vt.sh │ └── train_images_gen_vt │ │ ├── llava_instruct_mix665k_coco_gen_vt.sh │ │ ├── llava_instruct_mix665k_ocrvqa_gen_vt.sh │ │ ├── llava_instruct_mix665k_textcap_gen_vt.sh │ │ ├── llava_instruct_mix665k_vg_gen_vt.sh │ │ └── merge_llava_instruct_mix665k_all_gen_vt.py └── train │ ├── finetune_VTGenerator-13B.sh │ └── pretrain_VTGenerator-Pretrained-13B.sh ├── 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 ├── gpt_eval ├── multi_gpt_eval_gqa.sh ├── multi_gpt_eval_mmmu.sh └── multi_gpt_eval_mmvp.sh ├── merge_lora_weights.py ├── pretrain.sh ├── pretrain_xformers.sh ├── sqa_eval_batch.sh ├── sqa_eval_gather.sh ├── v1_5 ├── eval │ ├── gqa.sh │ ├── llavabench.sh │ ├── mmbench.sh │ ├── mmbench_cn.sh │ ├── mme.sh │ ├── 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