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# coding=utf-8 # Copyright 2022 Meta and The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # #...
transformers/src/transformers/models/timesformer/modeling_timesformer.py/0
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358
# coding=utf-8 # Copyright 2023 The Intel AIA Team Authors, and HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License=, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/lice...
transformers/src/transformers/models/tvp/configuration_tvp.py/0
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359
# coding=utf-8 # Copyright 2021 The Fairseq Authors and The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/...
transformers/src/transformers/models/unispeech/configuration_unispeech.py/0
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360
# coding=utf-8 # Copyright 2022 The HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable...
transformers/src/transformers/models/upernet/convert_swin_upernet_to_pytorch.py/0
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361
# coding=utf-8 # Copyright 2023 Microsoft Research & University of Wisconsin-Madison and the HuggingFace Inc. team. All rights reserved. # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # ...
transformers/src/transformers/models/vipllava/configuration_vipllava.py/0
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362
# coding=utf-8 # Copyright 2021 The HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable...
transformers/src/transformers/models/visual_bert/convert_visual_bert_original_pytorch_checkpoint_to_pytorch.py/0
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363
# coding=utf-8 # Copyright 2023 HUST-VL and The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 ...
transformers/src/transformers/models/vitmatte/modeling_vitmatte.py/0
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# coding=utf-8 # Copyright 2021 The Fairseq Authors and the HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/...
transformers/src/transformers/models/wav2vec2/modeling_flax_wav2vec2.py/0
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365
# coding=utf-8 # Copyright 2022 The HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable...
transformers/src/transformers/models/whisper/processing_whisper.py/0
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366
# coding=utf-8 # Copyright 2018 The Google AI Language Team Authors and The HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICEN...
transformers/src/transformers/optimization.py/0
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367
# coding=utf-8 # Copyright 2024 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/src/transformers/pipelines/image_to_text.py/0
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368
from typing import Any, Dict, List, Union from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends from .base import ChunkPipeline, build_pipeline_init_args if is_vision_available(): from PIL import Image from ..image_utils import load_image if is_torch_av...
transformers/src/transformers/pipelines/zero_shot_object_detection.py/0
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369
# Copyright 2021 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
transformers/src/transformers/sagemaker/training_args_sm.py/0
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370
#!/usr/bin/env python # coding=utf-8 # Copyright 2023 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/L...
transformers/src/transformers/tools/prompts.py/0
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371
#!/usr/bin/env python # coding=utf-8 # Copyright 2021 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/L...
transformers/src/transformers/utils/__init__.py/0
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372
# This file is autogenerated by the command `make fix-copies`, do not edit. from ..utils import DummyObject, requires_backends class AlbertTokenizerFast(metaclass=DummyObject): _backends = ["tokenizers"] def __init__(self, *args, **kwargs): requires_backends(self, ["tokenizers"]) class BartTokenize...
transformers/src/transformers/utils/dummy_tokenizers_objects.py/0
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373
<!--- Copyright 2022 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or ...
transformers/templates/adding_a_missing_tokenization_test/README.md/0
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374
# coding=utf-8 # Copyright 2022 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/templates/adding_a_new_model/cookiecutter-template-{{cookiecutter.modelname}}/test_modeling_{{cookiecutter.lowercase_modelname}}.py/0
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375
# coding=utf-8 # Copyright 2023 The HuggingFace Team Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a clone of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable...
transformers/tests/generation/test_streamers.py/0
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376
# coding=utf-8 # Copyright 2022 HuggingFace Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or ag...
transformers/tests/models/audio_spectrogram_transformer/test_feature_extraction_audio_spectrogram_transformer.py/0
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377
# Copyright 2023 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
transformers/tests/models/bark/test_processor_bark.py/0
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378
# coding=utf-8 # Copyright 2023 The Intel Labs Team Authors, The Microsoft Research Team Authors and HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License a...
transformers/tests/models/bridgetower/test_modeling_bridgetower.py/0
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379
# coding=utf-8 # Copyright 2023 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/clvp/test_modeling_clvp.py/0
{ "file_path": "transformers/tests/models/clvp/test_modeling_clvp.py", "repo_id": "transformers", "token_count": 11723 }
380
# coding=utf-8 # Copyright 2021 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/convbert/test_modeling_tf_convbert.py/0
{ "file_path": "transformers/tests/models/convbert/test_modeling_tf_convbert.py", "repo_id": "transformers", "token_count": 8020 }
381
# coding=utf-8 # Copyright 2018 Salesforce and HuggingFace Inc. team. # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by a...
transformers/tests/models/ctrl/test_tokenization_ctrl.py/0
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382
# coding=utf-8 # Copyright 2021 HuggingFace Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or ag...
transformers/tests/models/detr/test_image_processing_detr.py/0
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383
# coding=utf-8 # Copyright 2023 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/efficientnet/test_modeling_efficientnet.py/0
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384
# coding=utf-8 # Copyright 2023 The HuggingFace Inc. and Baidu team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # ...
transformers/tests/models/ernie_m/test_modeling_ernie_m.py/0
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385
# coding=utf-8 # Copyright 2022 Meta Platforms authors and HuggingFace Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless requi...
transformers/tests/models/flava/test_image_processing_flava.py/0
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386
import unittest import numpy as np from transformers import is_torch_available, is_vision_available from transformers.testing_utils import ( require_torch, require_torchvision, require_vision, ) if is_torch_available() and is_vision_available(): import torch from transformers import FuyuImagePr...
transformers/tests/models/fuyu/test_image_processing_fuyu.py/0
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387
# coding=utf-8 # Copyright 2020 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless requir...
transformers/tests/models/gpt2/test_modeling_tf_gpt2.py/0
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388
# coding=utf-8 # Copyright 2022 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless requir...
transformers/tests/models/jukebox/test_tokenization_jukebox.py/0
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389
# coding=utf-8 # Copyright 2022 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/layoutlmv3/test_modeling_tf_layoutlmv3.py/0
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390
# Copyright 2023 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
transformers/tests/models/llama/test_modeling_flax_llama.py/0
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391
# coding=utf-8 # Copyright 2021 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/luke/test_modeling_luke.py/0
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392
# Copyright 2020 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
transformers/tests/models/mbart/test_tokenization_mbart.py/0
{ "file_path": "transformers/tests/models/mbart/test_tokenization_mbart.py", "repo_id": "transformers", "token_count": 6618 }
393
# coding=utf-8 # Copyright 2022 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/mobilevit/test_modeling_mobilevit.py/0
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394
# Copyright 2022 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
transformers/tests/models/opt/test_modeling_flax_opt.py/0
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395
# coding=utf-8 # Copyright 2023 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/pix2struct/test_modeling_pix2struct.py/0
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396
# coding=utf-8 # Copyright 2022 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/realm/test_modeling_realm.py/0
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397
# coding=utf-8 # Copyright 2021 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/roformer/test_modeling_roformer.py/0
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398
# coding=utf-8 # Copyright 2022 HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law...
transformers/tests/models/speech_encoder_decoder/test_modeling_flax_speech_encoder_decoder.py/0
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399
# coding=utf-8 # Copyright 2020 The HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable...
transformers/tests/models/tapas/test_modeling_tapas.py/0
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400
# coding=utf-8 # Copyright 2021 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/vision_text_dual_encoder/test_modeling_tf_vision_text_dual_encoder.py/0
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401
# coding=utf-8 # Copyright 2022 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/vit_msn/test_modeling_vit_msn.py/0
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402
# coding=utf-8 # Copyright 2021 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/wav2vec2/test_modeling_wav2vec2.py/0
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403
# coding=utf-8 # Copyright 2022 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/whisper/test_modeling_flax_whisper.py/0
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404
# Copyright 2020 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
transformers/tests/pipelines/test_pipelines_token_classification.py/0
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405
import argparse import logging import sys import time import tensorflow as tf from datasets import load_dataset from packaging.version import parse from transformers import AutoTokenizer, TFAutoModelForSequenceClassification try: import tf_keras as keras except (ModuleNotFoundError, ImportError): import ker...
transformers/tests/sagemaker/scripts/tensorflow/run_tf.py/0
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406
# Copyright 2020 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
transformers/tests/test_modeling_flax_utils.py/0
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# coding=utf-8 # Copyright 2023 HuggingFace Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or ag...
transformers/tests/tools/test_image_question_answering.py/0
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# Copyright 2020 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
transformers/tests/trainer/test_trainer_tpu.py/0
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# coding=utf-8 # Copyright 2022 HuggingFace Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or ag...
transformers/tests/utils/test_image_processing_utils.py/0
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# coding=utf-8 # Copyright 2023 The HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable...
transformers/utils/check_docstrings.py/0
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import argparse import math import traceback import dateutil.parser as date_parser import requests def extract_time_from_single_job(job): """Extract time info from a single job in a GitHub Actions workflow run""" job_info = {} start = job["started_at"] end = job["completed_at"] start_datetime ...
transformers/utils/get_github_job_time.py/0
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from transformers import CLIPImageProcessor class CustomImageProcessor(CLIPImageProcessor): pass
transformers/utils/test_module/custom_image_processing.py/0
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cff-version: 1.2.0 title: 'TRL: Transformer Reinforcement Learning' message: >- If you use this software, please cite it using the metadata from this file. type: software authors: - given-names: Leandro family-names: von Werra - given-names: Younes family-names: Belkada - given-names: Lewis family...
trl/CITATION.cff/0
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BENCHMARK_SCRIPT="benchmark/benchmark_level1.sh" \ BENCHMARK_PLOT_SCRIPT="benchmark/benchmark_level1_plot.sh" \ bash benchmark/benchmark_and_report.sh
trl/benchmark/regression_test.sh/0
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<div style="text-align: center"> <img src="https://huggingface.co/datasets/trl-internal-testing/example-images/resolve/main/images/trl_banner_dark.png"> </div> # TRL - Transformer Reinforcement Learning TRL is a full stack library where we provide a set of tools to train transformer language models with Reinforcement...
trl/docs/source/index.mdx/0
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# Use model after training Once you have trained a model using either the SFTTrainer, PPOTrainer, or DPOTrainer, you will have a fine-tuned model that can be used for text generation. In this section, we'll walk through the process of loading the fine-tuned model and generating text. If you need to run an inference se...
trl/docs/source/use_model.md/0
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<jupyter_start><jupyter_text>Tune GPT2 to generate positive reviews> Optimise GPT2 to produce positive IMDB movie reviews using a BERT sentiment classifier as a reward function. Figure: Experiment setup to tune GPT2. The yellow arrows are outside the scope of this notebook, but the trained models are available through...
trl/examples/notebooks/gpt2-sentiment.ipynb/0
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# Copyright 2023 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by appl...
trl/examples/research_projects/toxicity/scripts/gpt-j-6b-toxicity.py/0
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""" trl is an open library for RL with transformer models. Note: VERSION needs to be formatted following the MAJOR.MINOR.PATCH convention (we need to follow this convention to be able to retrieve versioned scripts) Simple check list for release from AllenNLP repo: https://github.com/allenai/allennlp/blob/maste...
trl/setup.py/0
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# Copyright 2024 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
trl/tests/test_kto_trainer.py/0
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# Copyright 2024 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
trl/trl/trainer/kto_config.py/0
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# Big model inference benchmarks Running inference with Accelerate on big models. ## Setup These benchmarks use the `transformers` library: ```bash pip install transformers ``` To reproduce or test a new setup, run ```py python inference_acc.py model_name ``` This script supports `gpt-j-6b`, `gpt-neox`, `opt` (3...
accelerate/benchmarks/README.md/0
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0
<!--Copyright 2023 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
accelerate/docs/source/basic_tutorials/troubleshooting.md/0
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<!--Copyright 2022 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
accelerate/docs/source/usage_guides/gradient_accumulation.md/0
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#!/usr/bin/env python # Copyright 2022 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # U...
accelerate/examples/by_feature/deepspeed_with_config_support.py/0
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# Copyright 2022 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
accelerate/manim_animations/big_model_inference/stage_5.py/0
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#!/usr/bin/env python # Copyright 2022 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unles...
accelerate/src/accelerate/commands/config/update.py/0
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5
# Copyright 2021 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
accelerate/src/accelerate/launchers.py/0
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# Copyright 2022 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
accelerate/src/accelerate/utils/imports.py/0
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# Copyright 2022 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
accelerate/tests/deepspeed/test_deepspeed.py/0
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# Copyright 2021 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
accelerate/tests/test_kwargs_handlers.py/0
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# Copyright 2021 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
accelerate/tests/test_utils.py/0
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# Language Adaptation through Continued Pretraining This directory shows a base example of how to use continued pretraining and further tuning to adapt a language model to new data (e.g. a new language or domain). Three steps are needed: continued pretraining (`cpt`), supervised finetuning (`sft`), and direct prefere...
alignment-handbook/recipes/gpt2-nl/README.md/0
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# Model arguments model_name_or_path: mistralai/Mistral-7B-v0.1 model_revision: main torch_dtype: float16 # LoRA arguments load_in_4bit: true use_peft: true lora_r: 16 lora_alpha: 16 lora_dropout: 0.05 lora_target_modules: - q_proj - k_proj - v_proj - o_proj - gate_proj - up_proj - down_proj # Data training arguments...
alignment-handbook/recipes/zephyr-7b-beta/sft/config_qlora.yaml/0
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# Writing a custom kernel
candle/candle-book/src/cuda/writing.md/0
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# Training Training starts with data. We're going to use the huggingface hub and start with the Hello world dataset of machine learning, MNIST. Let's start with downloading `MNIST` from [huggingface](https://huggingface.co/datasets/mnist). This requires [`hf-hub`](https://github.com/huggingface/hf-hub). ```bash ca...
candle/candle-book/src/training/training.md/0
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use crate::op::{BinaryOp, Op, ReduceOp, UnaryOp}; use crate::{Error, Result, Tensor, TensorId}; use std::collections::HashMap; // arg has been reduced to node via reduce_dims, expand it back to arg. // This has to handle keepdims. fn broadcast_back(arg: &Tensor, node: &Tensor, reduced_dims: &[usize]) -> Result<Tensor>...
candle/candle-core/src/backprop.rs/0
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#![allow(dead_code)] use crate::op::{BinaryOpT, CmpOp, ReduceOp, UnaryOpT}; use crate::{CpuStorage, DType, Error, Layout, Result, Shape}; #[derive(Debug, Clone)] pub struct MetalDevice; #[derive(Debug)] pub struct MetalStorage; #[derive(thiserror::Error, Debug)] pub enum MetalError { #[error("{0}")] Message(...
candle/candle-core/src/dummy_metal_backend.rs/0
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use super::utils::{ get_scale_min_k4, group_for_dequantization, group_for_quantization, make_q3_quants, make_qkx1_quants, make_qx_quants, nearest_int, }; use super::GgmlDType; use crate::Result; use byteorder::{ByteOrder, LittleEndian}; use half::f16; use rayon::prelude::*; // Default to QK_K 256 rather than 6...
candle/candle-core/src/quantized/k_quants.rs/0
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use anyhow::Result; use candle_core::{test_device, test_utils, Device, IndexOp, Tensor}; /* This test is based on the following script. import torch torch.manual_seed(4242) t = torch.randn((1, 4, 5)) w = torch.randn((2, 4, 3)) print(t.flatten()) print(w.flatten()) res = torch.nn.functional.conv1d(t, w) print(res.flat...
candle/candle-core/tests/conv_tests.rs/0
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#[cfg(feature = "mkl")] extern crate intel_mkl_src; #[cfg(feature = "accelerate")] extern crate accelerate_src; use candle_transformers::models::bert::{BertModel, Config, HiddenAct, DTYPE}; use anyhow::{Error as E, Result}; use candle::Tensor; use candle_nn::VarBuilder; use clap::Parser; use hf_hub::{api::sync::Api, ...
candle/candle-examples/examples/bert/main.rs/0
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#[cfg(feature = "mkl")] extern crate intel_mkl_src; #[cfg(feature = "accelerate")] extern crate accelerate_src; use candle_transformers::models::distilbert::{Config, DistilBertModel, DTYPE}; use anyhow::{Error as E, Result}; use candle::{Device, Tensor}; use candle_nn::VarBuilder; use clap::Parser; use hf_hub::{api::...
candle/candle-examples/examples/distilbert/main.rs/0
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use crate::model::{Cache, Config, Llama}; use candle::{DType, Device, Result}; use candle_datasets::nlp::tinystories::{Dataset, DatasetRandomIter}; use candle_nn::Optimizer; fn valid_loss( dataset: &Dataset, model: &Llama, args: &crate::TrainingCmd, device: &Device, cache: &mut Cache, ) -> Result<f...
candle/candle-examples/examples/llama2-c/training.rs/0
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#[cfg(feature = "mkl")] extern crate intel_mkl_src; #[cfg(feature = "accelerate")] extern crate accelerate_src; use anyhow::{Error as E, Result}; use clap::Parser; use candle_transformers::models::qwen2::{Config, Model}; use candle::{DType, Device, Tensor}; use candle_examples::token_output_stream::TokenOutputStrea...
candle/candle-examples/examples/qwen/main.rs/0
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## candle-rwkv The [RWKV model](https://wiki.rwkv.com/) is a recurrent neural network model with performance on par with transformer architectures. Several variants are available, candle implements the v5 and v6 versions and can be used with Eagle 7B([blog post](https://blog.rwkv.com/p/eagle-7b-soaring-past-transforme...
candle/candle-examples/examples/rwkv/README.md/0
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# candle-t5 ## Encoder-decoder example: ```bash $ cargo run --example t5 --release -- --model-id "t5-small" --prompt "translate to German: A beautiful candle." --decode ... Eine schöne Kerze. 9 tokens generated (2.42 token/s) ``` Variants such as [flan-t5](https://huggingface.co/google/flan-t5-small), [flan-ul2](ht...
candle/candle-examples/examples/t5/README.md/0
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#[cfg(feature = "mkl")] extern crate intel_mkl_src; #[cfg(feature = "accelerate")] extern crate accelerate_src; mod model; use model::{Multiples, YoloV8, YoloV8Pose}; use candle::{DType, Device, IndexOp, Result, Tensor}; use candle_nn::{Module, VarBuilder}; use candle_transformers::object_detection::{non_maximum_sup...
candle/candle-examples/examples/yolo-v8/main.rs/0
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#include "flash_fwd_launch_template.h" void run_mha_fwd(Flash_fwd_params &params, cudaStream_t stream, bool force_split_kernel=false) { FP16_SWITCH(!params.is_bf16, [&] { FWD_HEADDIM_SWITCH(params.d, [&] { // if (params.num_splits <= 1 && !force_split_kernel) { // If we don't set it num_splits ...
candle/candle-flash-attn/kernels/flash_api.cu/0
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#include "binary_op_macros.cuh" #include<stdint.h> #if __CUDA_ARCH__ >= 800 BINARY_OP(__nv_bfloat16, badd_bf16, x + y) BINARY_OP(__nv_bfloat16, bdiv_bf16, x / y) BINARY_OP(__nv_bfloat16, bmul_bf16, x * y) BINARY_OP(__nv_bfloat16, bsub_bf16, x - y) BINARY_OP(__nv_bfloat16, bmaximum_bf16, maxg(x, y)) BINARY_OP(__nv_bflo...
candle/candle-kernels/src/binary.cu/0
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#include <metal_stdlib> #define MAX(x, y) ((x) > (y) ? (x) : (y)) #define MIN(x, y) ((x) < (y) ? (x) : (y)) METAL_FUNC uint get_strided_index( uint idx, constant size_t &num_dims, constant size_t *dims, constant size_t *strides ) { uint strided_i = 0; for (uint d = 0; d < num_dims; d++) { ...
candle/candle-metal-kernels/src/binary.metal/0
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[package] name = "candle-nn" version.workspace = true edition.workspace = true description.workspace = true repository.workspace = true keywords.workspace = true categories.workspace = true license.workspace = true readme = "README.md" [dependencies] accelerate-src = { workspace = true, optional = true } candle = { wo...
candle/candle-nn/Cargo.toml/0
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use candle::{CpuStorage, Layout, Result, Shape, Tensor}; use rayon::prelude::*; /// Applies the softmax function to the input tensor, rescaling the element so that elements on /// a slice of fixed index on dimension `dim` are between 0 and 1 and sum to 1. /// /// ```rust /// use candle::{Tensor, Device, test_utils::to...
candle/candle-nn/src/ops.rs/0
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use std::io::Result; fn main() -> Result<()> { prost_build::compile_protos(&["src/onnx.proto3"], &["src/"])?; Ok(()) }
candle/candle-onnx/build.rs/0
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from dataclasses import dataclass from typing import Optional from candle.nn import Module, Embedding, LayerNorm, Linear, ModuleList from candle import Tensor import candle import candle.functional as F from typing import Tuple, Optional @dataclass class Config: vocab_size: int = 30522 hidden_size: int = 768 ...
candle/candle-pyo3/py_src/candle/models/bert.py/0
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#![allow(clippy::redundant_closure_call)] use pyo3::exceptions::{PyTypeError, PyValueError}; use pyo3::prelude::*; use pyo3::pyclass::CompareOp; use pyo3::types::{IntoPyDict, PyDict, PyTuple}; use pyo3::ToPyObject; use std::collections::hash_map::DefaultHasher; use std::hash::{Hash, Hasher}; use std::os::raw::c_long; u...
candle/candle-pyo3/src/lib.rs/0
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use candle::{DType, Error, Result, Tensor}; use rand::{distributions::Distribution, SeedableRng}; pub struct LogitsProcessor { rng: rand::rngs::StdRng, temperature: Option<f64>, top_p: Option<f64>, } impl LogitsProcessor { pub fn new(seed: u64, temperature: Option<f64>, top_p: Option<f64>) -> Self { ...
candle/candle-transformers/src/generation/mod.rs/0
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