mirror of
https://github.com/huggingface/transformers.git
synced 2025-07-13 17:48:22 +06:00
f33a0cebb3
* feat: run `add-new-model-like` * feat: add paligemma code with "copied from" * feat: add ColPaliProcessor * feat: add ColPaliModel * feat: add ColPaliConfig * feat: rename `ColPaliForConditionalGeneration` to `ColPaliModel` * fixup modeling colpali * fix: fix root import shortcuts * fix: fix `modeling_auto` dict * feat: comment out ColPali test file * fix: fix typos from `add-new-model-like` * feat: explicit the forward input args * feat: move everything to `modular_colpali.py` * fix: put back ColPaliProcesor * feat: add auto-generated files * fix: run `fix-copies` * fix: remove DOCStRING constants to make modular converter work * fix: fix typo + modular converter * fix: add missing imports * feat: no more errors when loading ColPaliModel * fix: remove unused args in forward + tweak doc * feat: rename `ColPaliModel` to `ColPaliForRetrieval` * fix: apply `fix-copies` * feat: add ColPaliProcessor to `modular_colpali` * fix: run make quality + make style * fix: remove duplicate line in configuration_auto * feat: make ColPaliModel inehrit from PaliGemmaForConditionalGeneration * fix: tweak and use ColPaliConfig * feat: rename `score` to `post_process_retrieval` * build: run modular formatter + make style * feat: convert colpali weights + fixes * feat: remove old weight converter file * feat: add and validate tests * feat: replace harcoded path to "vidore/colpali-v1.2-hf" in tests * fix: add bfloat16 conversion in weight converter * feat: replace pytest with unittest in modeling colpali test * feat: add sanity check for weight conversion (doesn't work yet) * feat: add shape sanity check in weigth converter * feat: make ColPaliProcessor args explicit * doc: add doc for ColPali * fix: trying to fix output mismatch * feat: tweaks * fix: ColPaliModelOutput inherits from ModelOutput instead of PaliGemmaCausalLMOutputWithPast * fix: address comments on PR * fix: adapt tests to the Hf norm * wip: try things * feat: add `__call__` method to `ColPaliProcessor` * feat: remove need for dummy image in `process_queries` * build: run new modular converter * fix: fix incorrect method override * Fix tests, processing, modular, convert * fix tokenization auto * hotfix: manually fix processor -> fixme once convert modular is fixed * fix: convert weights working * feat: rename and improve convert weight script * feat: tweaks * fest: remove `device` input for `post_process_retrieval` * refactor: remove unused `get_torch_device` * Fix all tests * docs: update ColPali model doc * wip: fix convert weights to hf * fix logging modular * docs: add acknowledgements in model doc * docs: add missing docstring to ColPaliProcessor * docs: tweak * docs: add doc for `ColPaliForRetrievalOutput.forward` * feat: add modifications from colpali-engine v0.3.2 in ColPaliProcessor * fix: fix and upload colapli hf weights * refactor: rename `post_process_retrieval` to `score_retrieval` * fix: fix wrong typing for `score_retrieval` * test: add integration test for ColPali * chore: rerun convert modular * build: fix root imports * Update docs/source/en/index.md Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com> * fix: address PR comments * wip: reduce the prediction gap in weight conversion * docs: add comment in weight conversion script * docs: add example for `ColPaliForRetrieval.forward` * tests: change dataset path to the new one in hf-internal * fix: colpali weight conversion works * test: add fine-grained check for ColPali integration test * fix: fix typos in convert weight script * docs: move input docstring in a variable * fix: remove hardcoded torch device in test * fix: run the new modular refactor * docs: fix python example for ColPali * feat: add option to choose `score_retrieval`'s output dtype and device * docs: update doc for `score_retrieval` * feat: add `patch_size` property in ColPali model * chore: run `make fix-copies` * docs: update description for ColPali cookbooks * fix: remove `ignore_index` methods * feat: remove non-transformers specific methods * feat: update `__init__.py` to new hf format * fix: fix root imports in transformers * feat: remove ColPali's inheritance from PaliGemma * Fix CI issues * nit remove prints * feat: remove ColPali config and model from `modular_colpali.py` * feat: add `ColPaliPreTrainedModel` and update modeling and configuration code * fix: fix auto-removed imports in root `__init__.py` * fix: various fixes * fix: fix `_init_weight` * temp: comment `AutoModel.from_config` for experiments * fix: add missing `output_attentions` arg in ColPali's forward * fix: fix `resize_token_embeddings` * fix: make `input_ids` optional in forward * feat: rename `projection_layer` to `embedding_proj_layer` * wip: fix convert colpali weight script * fix tests and convert weights from original repo * fix unprotected import * fix unprotected torch import * fix style * change vlm_backbone_config to vlm_config * fix unprotected import in modular this time * fix: load config from Hub + tweaks in convert weight script * docs: move example usage from model docstring to model markdown * docs: fix input docstring for ColPali's forward method * fix: use `sub_configs` for ColPaliConfig * fix: remove non-needed sanity checks in weight conversion script + tweaks * fix: fix issue with `replace_return_docstrings` in ColPali's `forward` * docs: update docstring for `ColPaliConfig` * test: change model path in ColPali test * fix: fix ColPaliConfig * fix: fix weight conversion script * test: fix expected weights for ColPali model * docs: update ColPali markdown * docs: fix minor typo in ColPaliProcessor * Fix tests and add _no_split_modules * add text_config to colpali config * [run slow] colpali * move inputs to torch_device in integration test * skip test_model_parallelism * docs: clarify quickstart snippet in ColPali's model card * docs: update ColPali's model card --------- Co-authored-by: yonigozlan <yoni.gozlan@huggingface.co> Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com> |
||
|---|---|---|
| .. | ||
| internal | ||
| main_classes | ||
| model_doc | ||
| quantization | ||
| tasks | ||
| _config.py | ||
| _redirects.yml | ||
| _toctree.yml | ||
| accelerate.md | ||
| add_new_model.md | ||
| add_new_pipeline.md | ||
| agents_advanced.md | ||
| agents.md | ||
| attention.md | ||
| autoclass_tutorial.md | ||
| benchmarks.md | ||
| bertology.md | ||
| big_models.md | ||
| chat_templating.md | ||
| community.md | ||
| contributing.md | ||
| conversations.md | ||
| create_a_model.md | ||
| custom_models.md | ||
| debugging.md | ||
| deepspeed.md | ||
| fast_tokenizers.md | ||
| fsdp.md | ||
| generation_strategies.md | ||
| gguf.md | ||
| glossary.md | ||
| how_to_hack_models.md | ||
| hpo_train.md | ||
| index.md | ||
| installation.md | ||
| kv_cache.md | ||
| llm_optims.md | ||
| llm_tutorial_optimization.md | ||
| llm_tutorial.md | ||
| model_memory_anatomy.md | ||
| model_sharing.md | ||
| model_summary.md | ||
| modular_transformers.md | ||
| multilingual.md | ||
| notebooks.md | ||
| pad_truncation.md | ||
| peft.md | ||
| perf_hardware.md | ||
| perf_infer_cpu.md | ||
| perf_infer_gpu_multi.md | ||
| perf_infer_gpu_one.md | ||
| perf_torch_compile.md | ||
| perf_train_cpu_many.md | ||
| perf_train_cpu.md | ||
| perf_train_gpu_many.md | ||
| perf_train_gpu_one.md | ||
| perf_train_special.md | ||
| perf_train_tpu_tf.md | ||
| performance.md | ||
| perplexity.md | ||
| philosophy.md | ||
| pipeline_tutorial.md | ||
| pipeline_webserver.md | ||
| pr_checks.md | ||
| preprocessing.md | ||
| quicktour.md | ||
| run_scripts.md | ||
| sagemaker.md | ||
| serialization.md | ||
| task_summary.md | ||
| tasks_explained.md | ||
| testing.md | ||
| tf_xla.md | ||
| tflite.md | ||
| tiktoken.md | ||
| tokenizer_summary.md | ||
| torchscript.md | ||
| trainer.md | ||
| training.md | ||
| troubleshooting.md | ||