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* working version * fix copies * update * tests * update docs * codestyle * add more tests * add returns for docs * clean up * Update src/transformers/models/llava_onevision/processing_llava_onevision.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * updates * codestyle * style * shouldn't be reversed * [run-slow] llava_onevision * [run-slow] llava_onevision * add pooling in videos * [run-slow] llava_onevision * num-logits-to-keep * [run-slow] llava_onevision * [run-slow] llava_onevision * Update tests/test_modeling_common.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * video matched orig impl * fix tests * chat template was modified * Update docs/source/en/model_doc/llava_onevision.md Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * add morer info in the doc page --------- Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
…33195) * fix FM training kernels * fix copies * fix copies * propagate to slow path * make it BC * add comment * fix test
…models (#33226) * Fix `torch.jit.tracing` for `interpolate_pos_encoding` in all vision models * Apply formatting * Add missing `self.config = config` * Fix copies * Fix hiera interpolation unit test * Formatting * Update `_import_structure` * make style * Fix docstring * Use `# Copied from` instead of utils * DeiT variable renaming (`class_and_dist_pos_embed`) * Fix Hiera `interpolate_pos_encoding`
updated reporting a vulnerability section
* update gguf doc, config and tensor mapping * add qwen2moe architecture support, GGUFQwen2MoeConverter and q4 unit tests * apply code style fixes * reformat files * assign GGUFQwen2Converter to qwen2_moe
* qwen2vl_align_kv_seqlen_to_qwen2 * flash att test * [run-slow] qwen2_vl * [run-slow] qwen2_vl fix OOM * [run-slow] qwen2_vl * Update tests/models/qwen2_vl/test_modeling_qwen2_vl.py Co-authored-by: Raushan Turganbay <raushan.turganbay@alumni.nu.edu.kz> * Update tests/models/qwen2_vl/test_modeling_qwen2_vl.py Co-authored-by: Raushan Turganbay <raushan.turganbay@alumni.nu.edu.kz> * code quality --------- Co-authored-by: baishuai.bs <1051314669@qq.com> Co-authored-by: ShuaiBai623 <baishuai623@icloud.com> Co-authored-by: ShuaiBai623 <43326198+ShuaiBai623@users.noreply.github.com> Co-authored-by: Raushan Turganbay <raushan.turganbay@alumni.nu.edu.kz>
…#33319) add notebook for finetuning with mlflow Signed-off-by: Daniel Lok <daniel.lok@databricks.com>
squash commit
* add more cross-references * nit * import guard * more import guards * nit * Update src/transformers/generation/configuration_utils.py
* [whisper] alternative fix for long-form timestamps * update test
* fix-qwen2vl-vision-eager-attention * code-quality * Update src/transformers/models/qwen2_vl/modeling_qwen2_vl.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * code-quality --------- Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* support loading model without config.json file * fix condition * update tests * add test * ruff * ruff * ruff
…3196) * Add validation for maximum sequence length in modeling_whisper.py Added a validation check to ensure that the sequence length of labels does not exceed the maximum allowed length of 448 tokens. If the sequence length exceeds this limit, a ValueError is raised with a descriptive error message. This change prevents the model from encountering errors or unexpected behavior due to excessively long sequences during training or fine-tuning, ensuring consistent input dimensions and improving overall robustness. * Change exception message in src/transformers/models/whisper/modeling_whisper.py The exception message is for whisper's label's sequence max length. Co-authored-by: Yoach Lacombe <52246514+ylacombe@users.noreply.github.com> * Change 448 to config.max_target_positions in src/transformers/models/whisper/modeling_whisper.py It's for whisper's config.max_target_positions. Co-authored-by: Yoach Lacombe <52246514+ylacombe@users.noreply.github.com> * Change method's documentation in src/transformers/models/whisper/modeling_whisper.py * Add test for maximum label's sequence length in test_modeling_whisper.py * Add self to modeling_whisper.py * Update test_modeling_whisper.py with respect to automatic validations * Update modeling_whisper.py with respect to ci/circleci: check_code_quality * Update test_modeling_whisper.py with respect to ci/circleci: check_code_quality * Update test_modeling_whisper.py with respect to ci/circleci: tests_generate * Update test_modeling_whisper.py with respect to ci/circleci: tests_generate * Update test_modeling_whisper.py with respect to ci/circleci: check_code_quality * Separate test_labels_sequence_max_length tests in test_modeling_whisper.py * Update test_modeling_whisper.py with respect to ci/circleci: check_code_quality * Remove assert from test_modeling_whisper.py * Add max_target_positions to WhisperModelTester in test_modeling_whisper.py * Update test_modeling_whisper.py with respect to ci/circleci: check_code_quality * Update test_modeling_whisper.py with respect to ci/circleci: tests_generate * Update test_modeling_whisper.py * Change test_labels_sequence_max_length_error_after_changing_config in test_modeling_whisper.py * Change self.config.max_target_positions to self.max_target_positions modeling_whisper.py * Add new tests in test_modeling_whisper.py * Update test_modeling_whisper.py --------- Co-authored-by: Yoach Lacombe <52246514+ylacombe@users.noreply.github.com>
* add self.head_dim for VisionAttention in Qwen2-VL * add self.head_dim for VisionAttention in Qwen2-VL * fix ci * black the test_modeling_qwen2_vl.py * use ruff to format test_modeling_qwen2_vl.py * [run-slow] qwen2_vl * use tying for python3.8 * fix the import format * use ruff to fix the ci error I001 * [run-slow] qwen2_vl * remove unused import * commit for rebase * use ruff fix ci * [run-slow] qwen2_vl --------- Co-authored-by: root <liji>
* support 3D/4D attention mask in bert * test cases * update doc * fix doc
* use existing TikTokenConverter to read tiktoken tokenizer.model file * del test file * create titktoken integration file * adding tiktoken llama test * ALTNATIVE IMPLEMENTATION: supports llama 405B * fix one char * remove redundant line * small fix * rm unused import * flag for converting from tiktokeng * remove unneeded file * ruff * remove llamatiktokenconverter, stick to general converter * tiktoken support v2 * update test * remove stale changes * udpate doc * protect import * use is_protobuf_available * add templateprocessor in tiktokenconverter * reverting templateprocessor from tiktoken support * update test * add require_tiktoken * dev-ci * trigger build * trigger build again * dev-ci * [build-ci-image] tiktoken * dev-ci * dev-ci * dev-ci * dev-ci * change tiktoken file name * feedback review * feedback rev * applying feedback, removing tiktoken converters * conform test * adding docs for review * add doc file for review * add doc file for review * add doc file for review * support loading model without config.json file * Revert "support loading model without config.json file" This reverts commit 2753602. * remove dev var * updating docs * safely import protobuf * fix protobuf import error * fix protobuf import error * trying isort to fix ruff error * fix ruff error * try to fix ruff again * try to fix ruff again * try to fix ruff again * doc table of contents * add fix for consistency.dockerfile torchaudio * ruff * applying feedback * minor typo * merging with push-ci-image * clean up imports * revert dockerfile consistency
* fix copies * ???
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