├── .gitignore ├── DiffusionDPO ├── data_generation.py ├── inference.py ├── launchers │ └── turbo_dpo.sh ├── requirements.txt ├── sift_dpo_data.py └── train.py ├── LICENSE ├── README.md ├── UnifiedReward-Edit ├── edit_pairwise_rank.py ├── edit_paiwise_score.py ├── edit_pointwise_instruction_following.py ├── edit_pointwise_quality.py ├── vllm_request.py └── vllm_server.sh ├── UnifiedReward-Think ├── 0.cold_start.sh ├── 1.rejection_sampling.sh ├── 2.grpo.sh ├── 2.multi_node_grpo.sh ├── README.md ├── benchmark_evaluation │ ├── GenAI-Bench-Image │ │ ├── test_llava_answer_genAI_bench_image.py │ │ ├── test_llava_cot_genAI_bench_image.py │ │ ├── test_qwen25_answer_genAI_bench_image.py │ │ └── test_qwen25_cot_genAI_bench_image.py │ ├── GenAI-Bench-Video │ │ ├── data.json │ │ ├── test_llava_answer_genAI_bench_video.py │ │ ├── test_llava_cot_genAI_bench_video.py │ │ ├── test_qwen25_answer_genAI_bench_video.py │ │ └── test_qwen25_cot_genAI_bench_video.py │ ├── VL-RewardBench │ │ ├── data.json │ │ ├── test_llava_answer_vl_rewardbench.py │ │ ├── test_llava_cot_vl_rewardbench.py │ │ ├── test_qwen25_answer_vl_rewardbench.py │ │ └── test_qwen25_cot_vl_rewardbench.py │ ├── VideoGen-RewardBench │ │ ├── test_llava_answer_videogen_reward_bench.py │ │ ├── test_llava_cot_videogen_reward_bench.py │ │ ├── test_qwen25_answer_videogen_reward_bench.py │ │ └── test_qwen25_cot_videogen_reward_bench.py │ └── vLLM_qwen3_evaluation │ │ ├── README.md │ │ ├── test_qwen3vl_genai_image.py │ │ ├── test_qwen3vl_genai_video.py │ │ ├── test_qwen3vl_videogen_rewardbench.py │ │ ├── test_qwen3vl_vlreward_bench.py │ │ ├── vllm_request.py │ │ └── vllm_server.sh ├── dataset │ ├── cold_start.yaml │ ├── grpo.yaml │ └── rejection_sampling.yaml ├── gradio │ ├── llava_app.py │ └── qwen_app.py ├── inference_llava │ ├── image_generation │ │ └── infer_cot_image_generation.py │ ├── image_understanding │ │ └── infer_cot_image_understanding.py │ ├── video_generation │ │ └── infer_cot_video_generation.py │ └── video_understanding │ │ └── infer_cot_video_understanding.py ├── inference_qwen │ ├── UnifiedReward-Think-qwen3vl-inference │ │ ├── README.md │ │ ├── qwen3vl_infer_cot_image_generation.py │ │ ├── qwen3vl_infer_cot_image_understanding.py │ │ ├── qwen3vl_infer_cot_video_generation.py │ │ ├── qwen3vl_infer_cot_video_understanding.py │ │ ├── vllm_request.py │ │ └── vllm_server.sh │ ├── image_generation │ │ └── qwen_infer_cot_image_generation.py │ ├── image_understanding │ │ └── qwen_infer_cot_image_understanding.py │ ├── video_generation │ │ └── qwen_infer_cot_video_generation.py │ └── video_understanding │ │ └── qwen_infer_cot_video_understanding.py ├── llava │ ├── __init__.py │ ├── constants.py │ ├── conversation.py │ ├── entry.py │ ├── eval │ │ ├── evaluate_interleave.py │ │ ├── mmmu_utils │ │ │ ├── __pycache__ │ │ │ │ └── data_utils.cpython-310.pyc │ │ │ ├── answer_dict_val.json │ │ │ ├── configs │ │ │ │ └── llava1.5.yaml │ │ │ ├── data_utils.py │ │ │ ├── eval_utils.py │ │ │ ├── merge_jsons.py │ │ │ └── model_utils.py │ │ └── model_vqa.py │ ├── mm_utils.py │ ├── modals.py │ ├── model │ │ ├── __init__.py │ │ ├── apply_delta.py │ │ ├── builder.py │ │ ├── consolidate.py │ │ ├── language_model │ │ │ ├── llava_gemma.py │ │ │ ├── llava_llama.py │ │ │ ├── llava_mistral.py │ │ │ ├── llava_mixtral.py │ │ │ ├── llava_mpt.py │ │ │ ├── llava_qwen.py │ │ │ ├── llava_qwen_moe.py │ │ │ └── modeling_llama.py │ │ ├── llava_arch.py │ │ ├── make_delta.py │ │ ├── multimodal_encoder │ │ │ ├── builder.py │ │ │ ├── clip_encoder.py │ │ │ ├── dev_eva_clip │ │ │ │ ├── eva_clip │ │ │ │ │ ├── __init__.py │ │ │ │ │ ├── bpe_simple_vocab_16e6.txt.gz │ │ │ │ │ ├── constants.py │ │ │ │ │ ├── eva_vit_model.py │ │ │ │ │ ├── factory.py │ │ │ │ │ ├── hf_configs.py │ │ │ │ │ ├── hf_model.py │ │ │ │ │ ├── loss.py │ │ │ │ │ ├── model.py │ │ │ │ │ ├── model_configs │ │ │ │ │ │ ├── EVA-CLIP-18B.json │ │ │ │ │ │ ├── EVA-CLIP-8B-plus.json │ │ │ │ │ │ ├── EVA-CLIP-8B.json │ │ │ │ │ │ ├── EVA01-CLIP-B-16.json │ │ │ │ │ │ ├── EVA01-CLIP-g-14-plus.json │ │ │ │ │ │ ├── EVA01-CLIP-g-14.json │ │ │ │ │ │ ├── EVA02-CLIP-B-16.json │ │ │ │ │ │ ├── EVA02-CLIP-L-14-336.json │ │ │ │ │ │ ├── EVA02-CLIP-L-14.json │ │ │ │ │ │ ├── EVA02-CLIP-bigE-14-plus.json │ │ │ │ │ │ ├── EVA02-CLIP-bigE-14.json │ │ │ │ │ │ ├── Internal-EVA02-CLIP-10B-14-448.json │ │ │ │ │ │ └── Internal-EVA02-CLIP-10B-14.json │ │ │ │ │ ├── modified_resnet.py │ │ │ │ │ ├── openai.py │ │ │ │ │ ├── pretrained.py │ │ │ │ │ ├── rope.py │ │ │ │ │ ├── timm_model.py │ │ │ │ │ ├── tokenizer.py │ │ │ │ │ ├── transform.py │ │ │ │ │ ├── transformer.py │ │ │ │ │ └── utils.py │ │ │ │ └── eva_vit.py │ │ │ ├── eva_clip │ │ │ │ ├── eva_clip_encoder.py │ │ │ │ ├── eva_clip_processors.py │ │ │ │ ├── eva_vit.py │ │ │ │ ├── factory.py │ │ │ │ └── model_configs │ │ │ │ │ ├── EVA-CLIP-18B.json │ │ │ │ │ ├── EVA-CLIP-8B-plus.json │ │ │ │ │ ├── EVA-CLIP-8B.json │ │ │ │ │ ├── EVA01-CLIP-B-16.json │ │ │ │ │ ├── EVA01-CLIP-g-14-plus.json │ │ │ │ │ ├── EVA01-CLIP-g-14.json │ │ │ │ │ ├── EVA02-CLIP-B-16.json │ │ │ │ │ ├── EVA02-CLIP-L-14-336.json │ │ │ │ │ ├── EVA02-CLIP-L-14.json │ │ │ │ │ ├── EVA02-CLIP-bigE-14-plus.json │ │ │ │ │ ├── EVA02-CLIP-bigE-14.json │ │ │ │ │ ├── Internal-EVA02-CLIP-10B-14-448.json │ │ │ │ │ └── Internal-EVA02-CLIP-10B-14.json │ │ │ ├── hf_vision.py │ │ │ ├── imagebind.py │ │ │ ├── open_clip_encoder.py │ │ │ ├── siglip_encoder.py │ │ │ └── vision_encoder.py │ │ ├── multimodal_projector │ │ │ ├── builder.py │ │ │ └── pooler_projector.py │ │ ├── multimodal_resampler │ │ │ ├── builder.py │ │ │ ├── masked_drop.py │ │ │ ├── perceiver.py │ │ │ ├── qformer.py │ │ │ └── spatial_pool.py │ │ └── utils.py │ ├── serve │ │ ├── __init__.py │ │ ├── cli.py │ │ ├── controller.py │ │ ├── examples │ │ │ ├── extreme_ironing.jpg │ │ │ └── waterview.jpg │ │ ├── gradio_multi_image.py │ │ ├── gradio_web_server.py │ │ ├── model_worker.py │ │ ├── register_worker.py │ │ ├── sglang_worker.py │ │ └── test_message.py │ ├── train │ │ ├── llava_grpo_trainer.py │ │ ├── llava_trainer.py │ │ ├── llava_trainer_eval.py │ │ ├── sequence_parallel │ │ │ ├── __init__.py │ │ │ ├── all_to_all.py │ │ │ ├── globals.py │ │ │ ├── hybrid_attn.py │ │ │ ├── input_utils.py │ │ │ ├── monkey_patch.py │ │ │ ├── ring │ │ │ │ ├── __init__.py │ │ │ │ ├── ring_flash_attn.py │ │ │ │ ├── ring_flash_attn_varlen.py │ │ │ │ ├── stripe_flash_attn.py │ │ │ │ ├── triton_utils.py │ │ │ │ ├── utils.py │ │ │ │ ├── zigzag_ring_flash_attn.py │ │ │ │ └── zigzag_ring_flash_attn_varlen.py │ │ │ └── ulysses_attn.py │ │ ├── train.py │ │ ├── train_grpo.py │ │ └── train_mem.py │ ├── utils.py │ ├── utils │ │ ├── __init__.py │ │ ├── distributed.py │ │ ├── io.py │ │ ├── merge_lora_weights_and_save_hf_model.py │ │ ├── tokenizer.py │ │ └── utils.py │ └── wids │ │ ├── __init__.py │ │ ├── wids.py │ │ ├── wids_bench.py │ │ ├── wids_cleanup.py │ │ ├── wids_dir.py │ │ ├── wids_dl.py │ │ ├── wids_index.py │ │ ├── wids_lru.py │ │ ├── wids_mmtar.py │ │ ├── wids_specs.py │ │ └── wids_tar.py ├── modules │ ├── __init__.py │ └── datasets_modules │ │ └── __init__.py ├── qwen_grpo.sh ├── scripts │ ├── archived │ │ ├── convert_gqa_for_eval.py │ │ ├── convert_mmvet_for_eval.py │ │ ├── convert_sqa_to_llava.py │ │ ├── convert_sqa_to_llava_base_prompt.py │ │ ├── convert_vizwiz_for_submission.py │ │ ├── convert_vqav2_for_submission.py │ │ ├── data_info.py │ │ ├── dpo_data_info.py │ │ ├── entry_cmd.sh │ │ ├── finetune.sh │ │ ├── finetune_1.5.sh │ │ ├── finetune_full_schedule.sh │ │ ├── finetune_lora.sh │ │ ├── finetune_mixtral.sh │ │ ├── finetune_mixtral_1.5.sh │ │ ├── finetune_mixtral_1.6_336px_anyres.sh │ │ ├── finetune_mixtral_1.6_336px_anyres_freeze_vision.sh │ │ ├── finetune_mixtral_1.6_336px_anyres_lmms_eval.sh │ │ ├── finetune_mixtral_copy.sh │ │ ├── finetune_qlora.sh │ │ ├── finetune_sqa.sh │ │ ├── merge_lora_weights.py │ │ ├── pretrain.sh │ │ ├── quick_check.py │ │ ├── sqa_eval_batch.sh │ │ └── sqa_eval_gather.sh │ ├── interleave │ │ ├── eval_all.sh │ │ ├── eval_interleave_3d.sh │ │ └── eval_multiprocess.sh │ ├── qwen.py │ ├── summarize_data.py │ ├── train │ │ ├── README.md │ │ ├── direct_finetune_clip.sh │ │ ├── direct_finetune_siglip_a4.sh │ │ ├── dpo.sh │ │ ├── dpo_ov7b.sh │ │ ├── finetune_ov.sh │ │ ├── finetune_si.sh │ │ ├── mid_stage.yaml │ │ ├── onevision.yaml │ │ ├── pretrain_clip.sh │ │ ├── pretrain_siglip.sh │ │ └── single_image.yaml │ ├── video │ │ ├── demo │ │ │ └── video_demo.sh │ │ ├── eval │ │ │ ├── activitynet_eval.sh │ │ │ ├── video_chatgpt_benchmark_eval_shard.sh │ │ │ ├── video_description_from_t2v.sh │ │ │ ├── video_detail_description_eval_only.sh │ │ │ └── video_detail_description_eval_shard.sh │ │ └── train │ │ │ ├── SO400M_Qwen2_72B_ov_to_video_am9.sh │ │ │ ├── SO400M_Qwen2_7B_ov_to_video_am9.sh │ │ │ └── exp.yaml │ ├── zero2.json │ ├── zero2_fused_adamw.json │ ├── zero2_offload.json │ ├── zero3.json │ ├── zero3_offload.json │ └── zero3pp.json ├── setup.cfg ├── setup.py ├── src │ └── open_r1 │ │ ├── __init__.py │ │ ├── grpo.py │ │ └── trainer │ │ ├── __init__.py │ │ └── grpo_trainer.py └── vllm_qwen │ ├── vllm_inference.py │ └── vllm_server.sh ├── VideoDPO ├── configs │ ├── inference │ │ ├── inference_t2v_1024_v1.0.yaml │ │ ├── inference_t2v_512_v2.0.yaml │ │ └── lora_inference_t2v_512_v2.0.yaml │ ├── inference_t2v_512_v2.0.yaml │ └── t2v_turbo_dpo │ │ ├── config.yaml │ │ └── vidpro │ │ └── train_data.yaml ├── data │ ├── base.py │ ├── lightning_data.py │ ├── video_data.py │ └── webvid_lvdm.py ├── data_generation.sh ├── inference.py ├── lvdm │ ├── distributions.py │ ├── ema.py │ ├── models │ │ ├── autoencoder.py │ │ ├── ddpm3d.py │ │ ├── turbo_utils │ │ │ ├── lora.py │ │ │ ├── lora_handler.py │ │ │ ├── ode_solver │ │ │ │ ├── __init__.py │ │ │ │ └── ddim_solver.py │ │ │ ├── t2v_turbo_pipeline.py │ │ │ ├── t2v_turbo_scheduler.py │ │ │ └── turbo_scheduler.py │ │ └── utils_diffusion.py │ ├── modules │ │ ├── ae_modules.py │ │ ├── attention.py │ │ ├── encoders │ │ │ ├── condition.py │ │ │ └── ip_resampler.py │ │ ├── lora.py │ │ ├── losses │ │ │ ├── __init__.py │ │ │ └── contperceptual.py │ │ ├── networks │ │ │ └── openaimodel3d.py │ │ ├── utils.py │ │ └── x_transformer.py │ └── samplers │ │ └── ddim.py ├── requirements.txt ├── run.sh ├── scripts │ ├── custom_train_utils.py │ ├── inference.py │ ├── inference_ddp.py │ ├── inference_utils.py │ ├── train.py │ ├── train_utils.py │ └── turbo_inference │ │ └── text2video.py ├── sift_dpo_data.py └── utils │ ├── callbacks.py │ ├── clean_results.py │ ├── common_utils.py │ ├── convert_pl_ckpt_lora.py │ ├── create_ref_model.py │ ├── load_weigths.py │ ├── save_video.py │ └── video2image.py ├── benchmark_evaluation ├── DPO_eval │ ├── MSRVTT-QA │ │ ├── msrvtt_infer.py │ │ └── test_qa.json │ ├── MSVD-QA │ │ ├── msvd_infer.py │ │ ├── test_qa.json │ │ └── youtube_mapping.txt │ ├── TGIF-QA │ │ ├── test_a.json │ │ ├── test_q.json │ │ └── tgif_infer.py │ └── eval_gpt.py ├── LLaVA_evaluation │ ├── test_llava_genAI_bench_image.py │ ├── test_llava_genAI_bench_video.py │ ├── test_llava_video_understanding_assessment.py │ ├── test_llava_videogen_reward_bench.py │ └── test_llava_vlrewardbench.py ├── Qwen_evaluation │ ├── test_qwen_genAI_bench_image.py │ ├── test_qwen_genAI_bench_video.py │ ├── test_qwen_videogen_reward_bench.py │ └── test_qwen_vlrewardbench.py └── vLLM_evaluation │ ├── README.md │ ├── test_qwen_genai_image.py │ ├── test_qwen_genai_video.py │ ├── test_qwen_videogen_rewardbench.py │ ├── test_qwen_vlreward_bench.py │ ├── vllm_request.py │ └── vllm_server.sh ├── dataset └── train_data.yaml ├── docs ├── Pref-GRPO.html ├── index.html ├── static │ ├── academicons.min.css │ ├── bulma-carousel.min.css │ ├── bulma-carousel.min.js │ ├── bulma-slider.min.css │ ├── bulma-slider.min.js │ ├── bulma.min.css │ ├── css │ ├── explorer-index.js │ ├── fontawesome.all.min.css │ ├── fontawesome.all.min.js │ ├── images │ │ ├── DPO_comparison.png │ │ ├── comared_reward_model.png │ │ ├── dataset_info.png │ │ ├── image_qualitative.png │ │ ├── intro.png │ │ ├── logo.png │ │ ├── logo_resize.png │ │ ├── pipeline.png │ │ ├── prefgrpo │ │ │ ├── pref_grpo_pipeline.png │ │ │ ├── pref_grpo_qualitative_1.png │ │ │ ├── pref_grpo_qualitative_2.png │ │ │ ├── pref_grpo_reward_hacking.png │ │ │ ├── pref_grpo_reward_hacking_ur.png │ │ │ ├── unigenbench_compare.png │ │ │ ├── unigenbench_evaluation_dimension.png │ │ │ ├── unigenbench_leadboard.png │ │ │ ├── unigenbench_performance.png │ │ │ ├── unigenbench_pipeline.png │ │ │ ├── unigenbench_prompt_theme.png │ │ │ ├── unigenbench_teaser.png │ │ │ └── unigenbench_testpoint_counts.png │ │ ├── quantitative_tables.png │ │ ├── think │ │ │ ├── ablation_image_understanding_results.png │ │ │ ├── ablation_vision_generation_results.png │ │ │ ├── gradio_case.png │ │ │ ├── image_understanding_results.png │ │ │ ├── more_image_generation_case.png │ │ │ ├── more_image_understanding_case.png │ │ │ ├── more_video_generation_case.png │ │ │ ├── more_video_understanding_case.png │ │ │ ├── pipeline_think.png │ │ │ ├── teaser.png │ │ │ ├── video_generation_case.png │ │ │ ├── vision_generation_case.png │ │ │ ├── vision_generation_results.png │ │ │ └── vision_understanding_case.png │ │ └── video_qualitative.png │ ├── index.css │ ├── leaderboard.css │ ├── leaderboard_testmini.js │ ├── question_card.js │ └── sort-table.js └── think.html ├── dpo_image_understand_ov7b.sh ├── dpo_video_understand_llava_video_7b.sh ├── inference_llava ├── image_generation │ ├── pair_rank_image_generation.py │ ├── point_score_ACS_image_generation.py │ └── point_score_image_generation.py ├── image_understanding │ ├── pair_rank_image_understanding.py │ └── point_score_image_understanding.py ├── video_generation │ ├── pair_rank_video_generation.py │ └── point_score_video_generation.py └── video_understanding │ ├── pair_rank_video_understanding.py │ └── point_score_video_understanding.py ├── inference_qwen ├── UnifiedReward-2.0-inference │ ├── README.md │ ├── pair_score_image_generation.py │ ├── pair_score_video_generation.py │ ├── point_score_ACS_image_generation.py │ ├── point_score_APS_video_generation.py │ ├── vllm_request.py │ └── vllm_server.sh ├── image_generation │ ├── qwen_pair_rank_image_generation.py │ ├── qwen_point_score_ACS_image_generation.py │ └── qwen_point_score_image_generation.py ├── image_understanding │ ├── qwen_pair_rank_image_understanding.py │ └── qwen_point_score_image_understanding.py ├── video_generation │ ├── qwen_pair_rank_video_generation.py │ └── qwen_point_score_video_generation.py └── video_understanding │ ├── qwen_pair_rank_video_understanding.py │ └── qwen_point_score_video_understanding.py ├── llava ├── __init__.py ├── constants.py ├── conversation.py ├── entry.py ├── eval │ ├── evaluate_interleave.py │ ├── mmmu_utils │ │ ├── __pycache__ │ │ │ └── data_utils.cpython-310.pyc │ │ ├── answer_dict_val.json │ │ ├── configs │ │ │ └── llava1.5.yaml │ │ ├── data_utils.py │ │ ├── eval_utils.py │ │ ├── merge_jsons.py │ │ └── model_utils.py │ └── model_vqa.py ├── mm_utils.py ├── modals.py ├── model │ ├── __init__.py │ ├── apply_delta.py │ ├── builder.py │ ├── consolidate.py │ ├── language_model │ │ ├── llava_gemma.py │ │ ├── llava_llama.py │ │ ├── llava_mistral.py │ │ ├── llava_mixtral.py │ │ ├── llava_mpt.py │ │ ├── llava_qwen.py │ │ ├── llava_qwen_moe.py │ │ └── modeling_llama.py │ ├── llava_arch.py │ ├── make_delta.py │ ├── multimodal_encoder │ │ ├── builder.py │ │ ├── clip_encoder.py │ │ ├── dev_eva_clip │ │ │ ├── eva_clip │ │ │ │ ├── __init__.py │ │ │ │ ├── bpe_simple_vocab_16e6.txt.gz │ │ │ │ ├── constants.py │ │ │ │ ├── eva_vit_model.py │ │ │ │ ├── factory.py │ │ │ │ ├── hf_configs.py │ │ │ │ ├── hf_model.py │ │ │ │ ├── loss.py │ │ │ │ ├── model.py │ │ │ │ ├── model_configs │ │ │ │ │ ├── EVA-CLIP-18B.json │ │ │ │ │ ├── EVA-CLIP-8B-plus.json │ │ │ │ │ ├── EVA-CLIP-8B.json │ │ │ │ │ ├── EVA01-CLIP-B-16.json │ │ │ │ │ ├── EVA01-CLIP-g-14-plus.json │ │ │ │ │ ├── EVA01-CLIP-g-14.json │ │ │ │ │ ├── EVA02-CLIP-B-16.json │ │ │ │ │ ├── EVA02-CLIP-L-14-336.json │ │ │ │ │ ├── EVA02-CLIP-L-14.json │ │ │ │ │ ├── EVA02-CLIP-bigE-14-plus.json │ │ │ │ │ ├── EVA02-CLIP-bigE-14.json │ │ │ │ │ ├── Internal-EVA02-CLIP-10B-14-448.json │ │ │ │ │ └── Internal-EVA02-CLIP-10B-14.json │ │ │ │ ├── modified_resnet.py │ │ │ │ ├── openai.py │ │ │ │ ├── pretrained.py │ │ │ │ ├── rope.py │ │ │ │ ├── timm_model.py │ │ │ │ ├── tokenizer.py │ │ │ │ ├── transform.py │ │ │ │ ├── transformer.py │ │ │ │ └── utils.py │ │ │ └── eva_vit.py │ │ ├── eva_clip │ │ │ ├── eva_clip_encoder.py │ │ │ ├── eva_clip_processors.py │ │ │ ├── eva_vit.py │ │ │ ├── factory.py │ │ │ └── model_configs │ │ │ │ ├── EVA-CLIP-18B.json │ │ │ │ ├── EVA-CLIP-8B-plus.json │ │ │ │ ├── EVA-CLIP-8B.json │ │ │ │ ├── EVA01-CLIP-B-16.json │ │ │ │ ├── EVA01-CLIP-g-14-plus.json │ │ │ │ ├── EVA01-CLIP-g-14.json │ │ │ │ ├── EVA02-CLIP-B-16.json │ │ │ │ ├── EVA02-CLIP-L-14-336.json │ │ │ │ ├── EVA02-CLIP-L-14.json │ │ │ │ ├── EVA02-CLIP-bigE-14-plus.json │ │ │ │ ├── EVA02-CLIP-bigE-14.json │ │ │ │ ├── Internal-EVA02-CLIP-10B-14-448.json │ │ │ │ └── Internal-EVA02-CLIP-10B-14.json │ │ ├── hf_vision.py │ │ ├── imagebind.py │ │ ├── open_clip_encoder.py │ │ ├── siglip_encoder.py │ │ └── vision_encoder.py │ ├── multimodal_projector │ │ ├── builder.py │ │ └── pooler_projector.py │ ├── multimodal_resampler │ │ ├── builder.py │ │ ├── masked_drop.py │ │ ├── perceiver.py │ │ ├── qformer.py │ │ └── spatial_pool.py │ └── utils.py ├── serve │ ├── __init__.py │ ├── cli.py │ ├── controller.py │ ├── examples │ │ ├── extreme_ironing.jpg │ │ └── waterview.jpg │ ├── gradio_multi_image.py │ ├── gradio_web_server.py │ ├── model_worker.py │ ├── register_worker.py │ ├── sglang_worker.py │ └── test_message.py ├── train │ ├── args.py │ ├── llama_flash_attn_monkey_patch.py │ ├── llava_trainer.py │ ├── llava_trainer_eval.py │ ├── sequence_parallel │ │ ├── __init__.py │ │ ├── __pycache__ │ │ │ ├── __init__.cpython-310.pyc │ │ │ ├── __init__.cpython-312.pyc │ │ │ ├── all_to_all.cpython-310.pyc │ │ │ ├── globals.cpython-310.pyc │ │ │ ├── globals.cpython-312.pyc │ │ │ ├── hybrid_attn.cpython-310.pyc │ │ │ ├── input_utils.cpython-310.pyc │ │ │ ├── monkey_patch.cpython-310.pyc │ │ │ └── ulysses_attn.cpython-310.pyc │ │ ├── all_to_all.py │ │ ├── globals.py │ │ ├── hybrid_attn.py │ │ ├── input_utils.py │ │ ├── monkey_patch.py │ │ ├── ring │ │ │ ├── __init__.py │ │ │ ├── __pycache__ │ │ │ │ ├── __init__.cpython-310.pyc │ │ │ │ ├── ring_flash_attn.cpython-310.pyc │ │ │ │ ├── ring_flash_attn_varlen.cpython-310.pyc │ │ │ │ ├── stripe_flash_attn.cpython-310.pyc │ │ │ │ ├── triton_utils.cpython-310.pyc │ │ │ │ ├── utils.cpython-310.pyc │ │ │ │ ├── zigzag_ring_flash_attn.cpython-310.pyc │ │ │ │ └── zigzag_ring_flash_attn_varlen.cpython-310.pyc │ │ │ ├── ring_flash_attn.py │ │ │ ├── ring_flash_attn_varlen.py │ │ │ ├── stripe_flash_attn.py │ │ │ ├── triton_utils.py │ │ │ ├── utils.py │ │ │ ├── zigzag_ring_flash_attn.py │ │ │ └── zigzag_ring_flash_attn_varlen.py │ │ └── ulysses_attn.py │ ├── train.py │ ├── train_dpo.py │ └── train_mem.py ├── utils.py ├── utils │ ├── __init__.py │ ├── distributed.py │ ├── io.py │ ├── merge_lora_weights_and_save_hf_model.py │ ├── tokenizer.py │ └── utils.py └── wids │ ├── __init__.py │ ├── wids.py │ ├── wids_bench.py │ ├── wids_cleanup.py │ ├── wids_dir.py │ ├── wids_dl.py │ ├── wids_index.py │ ├── wids_lru.py │ ├── wids_mmtar.py │ ├── wids_specs.py │ └── wids_tar.py ├── modules ├── __init__.py └── datasets_modules │ └── __init__.py ├── preference_data_construction ├── image_understanding │ └── infer+sift.py └── video_understanding │ └── infer+sift.py ├── pyproject.toml ├── scripts ├── archived │ ├── convert_gqa_for_eval.py │ ├── convert_mmvet_for_eval.py │ ├── convert_sqa_to_llava.py │ ├── convert_sqa_to_llava_base_prompt.py │ ├── convert_vizwiz_for_submission.py │ ├── convert_vqav2_for_submission.py │ ├── data_info.py │ ├── dpo_data_info.py │ ├── entry_cmd.sh │ ├── finetune.sh │ ├── finetune_1.5.sh │ ├── finetune_full_schedule.sh │ ├── finetune_lora.sh │ ├── finetune_mixtral.sh │ ├── finetune_mixtral_1.5.sh │ ├── finetune_mixtral_1.6_336px_anyres.sh │ ├── finetune_mixtral_1.6_336px_anyres_freeze_vision.sh │ ├── finetune_mixtral_1.6_336px_anyres_lmms_eval.sh │ ├── finetune_mixtral_copy.sh │ ├── finetune_qlora.sh │ ├── finetune_sqa.sh │ ├── merge_lora_weights.py │ ├── pretrain.sh │ ├── quick_check.py │ ├── sqa_eval_batch.sh │ └── sqa_eval_gather.sh ├── interleave │ ├── eval_all.sh │ ├── eval_interleave_3d.sh │ └── eval_multiprocess.sh ├── qwen.py ├── summarize_data.py ├── train │ ├── README.md │ ├── direct_finetune_clip.sh │ ├── direct_finetune_siglip_a4.sh │ ├── dpo.sh │ ├── dpo_ov7b.sh │ ├── finetune_ov.sh │ ├── finetune_si.sh │ ├── mid_stage.yaml │ ├── onevision.yaml │ ├── pretrain_clip.sh │ ├── pretrain_siglip.sh │ └── single_image.yaml ├── video │ ├── demo │ │ └── video_demo.sh │ ├── eval │ │ ├── activitynet_eval.sh │ │ ├── video_chatgpt_benchmark_eval_shard.sh │ │ ├── video_description_from_t2v.sh │ │ ├── video_detail_description_eval_only.sh │ │ └── video_detail_description_eval_shard.sh │ └── train │ │ ├── SO400M_Qwen2_72B_ov_to_video_am9.sh │ │ ├── SO400M_Qwen2_7B_ov_to_video_am9.sh │ │ └── exp.yaml ├── zero2.json ├── zero2_fused_adamw.json ├── zero2_offload.json ├── zero3.json ├── zero3_offload.json └── zero3pp.json ├── sglang_llava ├── sglang_inference.py └── sglang_server.sh ├── train.sh ├── trl ├── __init__.py ├── core.py ├── environment │ ├── __init__.py │ └── base_environment.py ├── extras │ ├── __init__.py │ ├── best_of_n_sampler.py │ └── dataset_formatting.py ├── import_utils.py ├── models │ ├── __init__.py │ ├── modeling_base.py │ ├── modeling_sd_base.py │ ├── modeling_value_head.py │ └── utils.py └── trainer │ ├── __init__.py │ ├── base.py │ ├── ddpo_config.py │ ├── ddpo_trainer.py │ ├── dpo_trainer.py │ ├── iterative_sft_trainer.py │ ├── model_config.py │ ├── ppo_config.py │ ├── ppo_trainer.py │ ├── reward_config.py │ ├── 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