├── LLaVA ├── .gitignore ├── LICENSE ├── README.md ├── finetune.sh ├── 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 │ │ ├── summarize_gpt_review.py │ │ ├── vqa_benchmark.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 │ │ │ └── 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 │ │ │ └── dino_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 ├── pretrain.sh ├── 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 │ └── pretrain.sh ├── README.md ├── imgs ├── mllm_results.png ├── teaser.png └── vlm_results.png ├── requirements.txt └── scripts ├── 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