- 05 Feb, 2025 4 commits
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ROZBEH authored
handle cases where it is list
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Liangliang Ma authored
* add xpu for unmask * change modular for generated matching * add lastest modeling for helium
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ManukyanD authored
* Fix synced multi-GPU generation * fix copies --------- Co-authored-by: Davit Manukyan <ManukyanD> Co-authored-by:
Raushan Turganbay <raushan@huggingface.co>
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ManukyanD authored
* Fix Gemma2 synced multi-GPU generation * Fix import ordering in modular_gemma2.py
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- 04 Feb, 2025 16 commits
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Yoni Gozlan authored
* add init and base image processing functions * add add_fast_image_processor to transformers-cli * add working fast image processor clip * add fast image processor to doc, working tests * remove "to be implemented" SigLip * fix unprotected import * fix unprotected vision import * update ViTImageProcessorFast * increase threshold slow fast ewuivalence * add fast img blip * add fast class in tests with cli * improve cli * add fast image processor convnext * add LlavaPatchingMixin and fast image processor for llava_next and llava_onevision * add device kwarg to ImagesKwargs for fast processing on cuda * cleanup * fix unprotected import * group images by sizes and add batch processing * Add batch equivalence tests, skip when center_crop is used * cleanup * update init and cli * fix-copies * refactor convnext, cleanup base * fix * remove patching mixins, add piped torchvision transforms for ViT * fix unbatched processing * fix f strings * protect imports * change llava onevision to class transforms (test) * fix convnext * improve formatting (following Pavel review) * fix handling device arg * improve cli * fix * fix inits * Add distinction between preprocess and _preprocess, and support for arbitrary kwargs through valid_extra_kwargs * uniformize qwen2_vl fast * fix docstrings * add add fast image processor llava * remove min_pixels max_pixels from accepted size * nit * nit * refactor fast image processors docstrings * cleanup and remove fast class transforms * update add fast image processor transformers cli * cleanup docstring * uniformize pixtral fast and make _process_image explicit * fix prepare image structure llava next/onevision * Use typed kwargs instead of explicit args * nit fix import Unpack * clearly separate pops and gets in base preprocess. Use explicit typed kwargs * make qwen2_vl preprocess arguments hashable
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David authored
* initial commit * encoder+decoder layer changes WIP * architecture checks * working version of detection + segmentation * fix modeling outputs * fix return dict + output att/hs * found the position embedding masking bug * pre-training version * added iamge processors * typo in init.py * iterupdate set to false * fixed num_labels in class_output linear layer bias init * multihead attention shape fixes * test improvements * test update * dab-detr model_doc update * dab-detr model_doc update2 * test fix:test_retain_grad_hidden_states_attentions * config file clean and renaming variables * config file clean and renaming variables fix * updated convert_to_hf file * small fixes * style and qulity checks * return_dict fix * Merge branch main into add_dab_detr * small comment fix * skip test_inputs_embeds test * image processor updates + image processor test updates * check copies test fix update * updates for check_copies.py test * updates for check_copies.py test2 * tied weights fix * fixed image processing tests and fixed shared weights issues * added numpy nd array option to get_Expected_values method in test_image_processing_dab_detr.py * delete prints from test file * SafeTensor modification to solve HF Trainer issue * removing the safetensor modifications * make fix copies and hf uplaod has been added. * fixed index.md * fixed repo consistency * styel fix and dabdetrimageprocessor docstring update * requested modifications after the first review * Update src/transformers/models/dab_detr/image_processing_dab_detr.py Co-authored-by:
Pavel Iakubovskii <qubvel@gmail.com> * repo consistency has been fixed * update copied NestedTensor function after main merge * Update src/transformers/models/dab_detr/modeling_dab_detr.py Co-authored-by:
Pavel Iakubovskii <qubvel@gmail.com> * temp commit * temp commit2 * temp commit 3 * unit tests are fixed * fixed repo consistency * updated expected_boxes varible values based on related notebook results in DABDETRIntegrationTests file. * temporarialy config modifications and repo consistency fixes * Put dilation parameter back to config * pattern embeddings have been added to the rename_keys method * add dilation comment to config + add as an exception in check_config_attributes SPECIAL CASES * delete FeatureExtractor part from docs.md * requested modifications in modeling_dab_detr.py * [run_slow] dab_detr * deleted last segmentation code part, updated conversion script and changed the hf path in test files * temp commit of requested modifications * temp commit of requested modifications 2 * updated config file, resolved codepaths and refactored conversion script * updated decodelayer block types and refactored conversion script * style and quality update * small modifications based on the request * attentions are refactored * removed loss functions from modeling file, added loss function to lossutils, tried to move the MLP layer generation to config but it failed * deleted imageprocessor * fixed conversion script + quality and style * fixed config_att * [run_slow] dab_detr * changing model path in conversion file and in test file * fix Decoder variable naming * testing the old loss function * switched back to the new loss function and testing with the odl attention functions * switched back to the new last good result modeling file * moved back to the version when I asked the review * missing new line at the end of the file * old version test * turn back to newest mdoel versino but change image processor * style fix * style fix after merge main * [run_slow] dab_detr * [run_slow] dab_detr * added device and type for head bias data part * [run_slow] dab_detr * fixed model head bias data fill * changed test_inference_object_detection_head assertTrues to torch test assert_close * fixes part 1 * quality update * self.bbox_embed in decoder has been restored * changed Assert true torch closeall methods to torch testing assertclose * modelcard markdown file has been updated * deleted intemediate list from decoder module --------- Co-authored-by:
Pavel Iakubovskii <qubvel@gmail.com>
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Yih-Dar authored
* update * update * update * dev-ci * more changes * fix * fix * fix --------- Co-authored-by:
ydshieh <ydshieh@users.noreply.github.com>
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Yih-Dar authored
update docker files Co-authored-by:
ydshieh <ydshieh@users.noreply.github.com>
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Luc Georges authored
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Yih-Dar authored
fix Co-authored-by:
ydshieh <ydshieh@users.noreply.github.com>
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Marc Sun authored
* add supports_quant_method check * fix * add test and fix suggestions * change logic slightly --------- Co-authored-by:
Mohamed Mekkouri <93391238+MekkCyber@users.noreply.github.com>
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Yih-Dar authored
* quantization CI on PRs * fix * fix * add 2 members --------- Co-authored-by:
ydshieh <ydshieh@users.noreply.github.com>
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pglorio authored
* First commit * Finish model implementation * First commit * Finish model implementation * Register zamba2 * generated modeling and configuration * generated modeling and configuration * added hybrid cache * fix attention_mask in mamba * dropped unused loras * fix flash2 * config docstrings * fix config and fwd pass * make fixup fixes * text_modeling_zamba2 * small fixes * make fixup fixes * Fix modular model converter * added inheritances in modular, renamed zamba cache * modular rebase * new modular conversion * fix generated modeling file * fixed import for Zamba2RMSNormGated * modular file cleanup * make fixup and model tests * dropped inheritance for Zamba2PreTrainedModel * make fixup and unit tests * Add inheritance of rope from GemmaRotaryEmbedding * moved rope to model init * drop del self.self_attn and del self.feed_forward * fix tests * renamed lora -> adapter * rewrote adapter implementation * fixed tests * Fix torch_forward in mamba2 layer * Fix torch_forward in mamba2 layer * Fix torch_forward in mamba2 layer * Dropped adapter in-place sum * removed rope from attention init * updated rope * created get_layers method * make fixup fix * make fixup fixes * make fixup fixes * update to new attention standard * update to new attention standard * make fixup fixes * minor fixes * cache_position * removed cache_position postion_ids use_cache * remove config from modular * removed config from modular (2) * import apply_rotary_pos_emb from llama * fixed rope_kwargs * Instantiate cache in Zamba2Model * fix cache * fix @slow decorator * small fix in modular file * Update docs/source/en/model_doc/zamba2.md Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com> * several minor fixes * inherit mamba2decoder fwd and drop position_ids in mamba * removed docstrings from modular * reinstate zamba2 attention decoder fwd * use regex for tied keys * Revert "use regex for tied keys" This reverts commit 9007a522b1f831df6d516a281c0d3fdd20a118f5. * use regex for tied keys * add cpu to slow forward tests * dropped config.use_shared_mlp_adapter * Update docs/source/en/model_doc/zamba2.md Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com> * re-convert from modular * extended Zamba2RMSNormGated to n_groups>1 * removed einops import * set _supports_sdpa = True * add use_mem_eff_path flag for fused mamba2 fwd * added docstring for use_mem_eff_ath flag --------- Co-authored-by:
root <root@node-2.us-southcentral1-a.compute.internal> Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com>
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Sumit Vij authored
* Fix device mismatch error in whisper feature extraction * Set default device * Address code review feedback --------- Co-authored-by:
eustlb <94853470+eustlb@users.noreply.github.com>
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Cyril Vallez authored
* start a nice modular * Update modular_gpt_neox.py * Update modular_gpt_neox.py * Update modular_gpt_neox.py * Update modular_gpt_neox.py * update * Update modular_gpt_neox.py * convert * fix attribute * fix attrs * oups * fix * fix * fix * fix * fix * fix order to pass test (see with accelerate team) * trigger CIs * modular * update * up * Update test_modeling_gpt_neox.py * Update test_modeling_gpt_neox.py * trigger CIs * correctly pass arg * simplify * remove key warning * update tp -> it's compatible since the view is before * trigger CIs
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Cyril Vallez authored
* Update convert_mistral_weights_to_hf.py * Update convert_mistral_weights_to_hf.py * update * style * move it to integrations * style * trigger CIs * trigger CIs
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Ryoo Kwangrok authored
* layernorm_decay_fix * W293 fix * ruff format fix * black format * ruff format * erase last layer * add test_get_parameter_names_rmsnorm * rmsnorm fix
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Dmitry Tarasov authored
apply_chat_template: consistent behaviour for return_assistant_tokens_mask=True return_tensors=True (#35582) * apply_chat_template: consistent return_tensors behaviour with return_assistant_tokens_mask flag * test_chat_template_return_assistant_tokens_mask: support tokenizers with no attention mask * test_chat_template_return_assistant_tokens_mask: skip tokenizers with no padding token * test_chat_template_return_assistant_tokens_mask: force tokenizer padding_side=right --------- Co-authored-by:
Eduard Allakhverdov <goncharova@airi.net> Co-authored-by:
d.tarasov <d.tarasov@airi.net>
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Pavel Iakubovskii authored
Updates type().is_cuda() -> .is_cuda(); .data<> -> .data_ptr<>
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Raushan Turganbay authored
* fix rope delats calculation * add test * style
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- 03 Feb, 2025 3 commits
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Alex Brooks authored
* Update granite vision model path Signed-off-by:
Alex-Brooks <Alex.brooks@ibm.com> * Enable granite vision test Signed-off-by:
Alex-Brooks <Alex.brooks@ibm.com> --------- Signed-off-by:
Alex-Brooks <Alex.brooks@ibm.com>
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Gar authored
* refine all resize_token_embedding() * ruff format * hotfix
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Arthur authored
* update test for now * up * cleanup * update todo
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- 31 Jan, 2025 4 commits
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Yih-Dar authored
use torch 2.6 for CI Co-authored-by:
ydshieh <ydshieh@users.noreply.github.com>
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Yoni Gozlan authored
* init modular got_ocr2 * Get correct got_ocr architecture * add processing * run modular with processing * add working inference * apply modular * Refactor and fix style * Refactor, cleanup, fix style * fix init order * Fix docs * add base modeling tests * fix style and consistency * rename doc file * fix repo consistency * fix inference with box * add image processing and support for crop_to_multi_page * Fix batch inference * add tests * fixup * fix slow test * fix docstrings * Add model doc * update to new init * fix input autocast pixel_values dtype * update doc * move doc to multimodal * Reformat crop_image_to_patches and add docstrings * Fix example in forward docstring * Address Pablo review * [run slow] got_ocr2 * remove defaults defined twice * apply modular * add torch_device to integration tests * update modular * follow-up Pavel review * add device variable in doc * fix doc multi-page * Force eager attention for vision encoder to avoid attn implementation conflict * revert qwen2vl doc changes * use Qwen2ForCausalLM instead of Qwen2Model * make fixup * refactor gotocr2 to llava style * uniformize function names and reduce checks * final nits * fix pixel_values dtype error * change checkpoint names * fix modular
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Joao Gante authored
moshi cant compile
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eustlb authored
compute head_dim_padding at init
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- 30 Jan, 2025 10 commits
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Yoni Gozlan authored
* move make_flat_list_of_images and make_batched_videos to image_utils * remove unnecessary is_vision_available * move make_nested_list_of_images to image_utils * fix fast pixtral image processor * fix import mllama * fix make_nested_list_of_images * add tests * convert 4d arrays/tensors to list * add test_make_batched_videos * add support nested batch of videos * fix image processing qwen2vl
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Marcel authored
* Handle empty change indices in RLE conversion for masks * [test] Add unit tests for RLE encoding of masks in SamProcessor * [test] Update RLE conversion tests to use TensorFlow implementation * [test] Fix formatting in SamProcessorTest according to check_code_quality action * [test] Fix formatting in SamProcessorTest according to check_code_quality * [test] Refactored rle test cases into one test and used tf tensors in tf test cases * [test] Fix: removed self parameter from refactored methods * [test] Removed nested methods in run-length encoding tests for PyTorch and TensorFlow * [test] Added description to individual to run-length encoding tests for PyTorch and TensorFlow.
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Yih-Dar authored
fix Co-authored-by:
ydshieh <ydshieh@users.noreply.github.com>
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Nat Jeffries authored
* Add support for attention masking in moonshine. Tested against Open ASR Leaderboard with batch size 256. * Update comments and ensure attention masks are passed everywhere. Perform attention mask downsampling inside of moonshine forward call. * Hide padding behind conditional. Fix encoder/decoder masking. - Correctly pipe encoder attention mask into decoder - Add correct scaling factor if one is not already provided. - Fix formatting with ruff * Add auto generated modeling_moonshine file. * Update formatting in generated model file. * Address review comments. * Fix typo. * Add `pad_head_dim_to_multiple_of` to moonshine config. * Correct args order for MooonshineConfig. * Update configuration moonshine too. * Update src/transformers/models/moonshine/modular_moonshine.py * Update src/transformers/models/moonshine/configuration_moonshine.py --------- Co-authored-by:
eustlb <94853470+eustlb@users.noreply.github.com>
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Yih-Dar authored
* fix * remove is_flaky * fix --------- Co-authored-by:
ydshieh <ydshieh@users.noreply.github.com>
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Matt authored
* p_mask back to being a list * Remove breakpoint
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Raushan Turganbay authored
* fix * remove overriden method * small change
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Raushan Turganbay authored
* initial POC * - batch mix feature * fix tests * fix tests * make style * do not skip and instead fix tests * update * return back the test * correct text with the correct ckpt
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Joao Gante authored
fix tests
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Ilyas Moutawwakil authored
* fix is_causal being a tensor * convert in sdpa attention only when jit tracing
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- 29 Jan, 2025 3 commits
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Wing Lian authored
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Joao Gante authored
* move max time tests to their right place * move test to the right place
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Boris Malashenko authored
There should be a dot after pip install .
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