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# 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/blenderbot_small/test_modeling_tf_blenderbot_small.py/0 | {
"file_path": "transformers/tests/models/blenderbot_small/test_modeling_tf_blenderbot_small.py",
"repo_id": "transformers",
"token_count": 4235
} | 446 |
# 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/tests/models/chameleon/test_modeling_chameleon.py/0 | {
"file_path": "transformers/tests/models/chameleon/test_modeling_chameleon.py",
"repo_id": "transformers",
"token_count": 8114
} | 447 |
# coding=utf-8
# Copyright 2022 The OpenBMB Team 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/LIC... | transformers/tests/models/cpmant/test_modeling_cpmant.py/0 | {
"file_path": "transformers/tests/models/cpmant/test_modeling_cpmant.py",
"repo_id": "transformers",
"token_count": 4314
} | 448 |
# 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/data2vec/test_modeling_tf_data2vec_vision.py/0 | {
"file_path": "transformers/tests/models/data2vec/test_modeling_tf_data2vec_vision.py",
"repo_id": "transformers",
"token_count": 9900
} | 449 |
# 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/tests/models/distilbert/test_modeling_flax_distilbert.py/0 | {
"file_path": "transformers/tests/models/distilbert/test_modeling_flax_distilbert.py",
"repo_id": "transformers",
"token_count": 2492
} | 450 |
# 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/dpt/test_modeling_dpt_auto_backbone.py/0 | {
"file_path": "transformers/tests/models/dpt/test_modeling_dpt_auto_backbone.py",
"repo_id": "transformers",
"token_count": 5379
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# 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/flaubert/test_modeling_flaubert.py/0 | {
"file_path": "transformers/tests/models/flaubert/test_modeling_flaubert.py",
"repo_id": "transformers",
"token_count": 8841
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# coding=utf-8
# Copyright 2020 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/funnel/test_modeling_funnel.py/0 | {
"file_path": "transformers/tests/models/funnel/test_modeling_funnel.py",
"repo_id": "transformers",
"token_count": 9059
} | 453 |
# 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/groupvit/test_modeling_groupvit.py/0 | {
"file_path": "transformers/tests/models/groupvit/test_modeling_groupvit.py",
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"token_count": 12775
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# 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/tests/models/jamba/test_modeling_jamba.py/0 | {
"file_path": "transformers/tests/models/jamba/test_modeling_jamba.py",
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# 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/lilt/test_modeling_lilt.py/0 | {
"file_path": "transformers/tests/models/lilt/test_modeling_lilt.py",
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# 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/longformer/test_modeling_longformer.py/0 | {
"file_path": "transformers/tests/models/longformer/test_modeling_longformer.py",
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"token_count": 15468
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# 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/mask2former/test_modeling_mask2former.py/0 | {
"file_path": "transformers/tests/models/mask2former/test_modeling_mask2former.py",
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"token_count": 8457
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# 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 ... | transformers/tests/models/mvp/test_modeling_mvp.py/0 | {
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"token_count": 15188
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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/models/oneformer/test_image_processing_oneformer.py/0 | {
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# 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/owlvit/test_modeling_owlvit.py/0 | {
"file_path": "transformers/tests/models/owlvit/test_modeling_owlvit.py",
"repo_id": "transformers",
"token_count": 15302
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# 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/perceiver/test_modeling_perceiver.py/0 | {
"file_path": "transformers/tests/models/perceiver/test_modeling_perceiver.py",
"repo_id": "transformers",
"token_count": 21243
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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... | transformers/tests/models/plbart/test_tokenization_plbart.py/0 | {
"file_path": "transformers/tests/models/plbart/test_tokenization_plbart.py",
"repo_id": "transformers",
"token_count": 6897
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# 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/pvt_v2/test_modeling_pvt_v2.py/0 | {
"file_path": "transformers/tests/models/pvt_v2/test_modeling_pvt_v2.py",
"repo_id": "transformers",
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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/models/rag/test_tokenization_rag.py/0 | {
"file_path": "transformers/tests/models/rag/test_tokenization_rag.py",
"repo_id": "transformers",
"token_count": 3143
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# 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/resnet/test_modeling_resnet.py/0 | {
"file_path": "transformers/tests/models/resnet/test_modeling_resnet.py",
"repo_id": "transformers",
"token_count": 4893
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# 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 | {
"file_path": "transformers/tests/models/roformer/test_modeling_roformer.py",
"repo_id": "transformers",
"token_count": 11336
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# 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/seamless_m4t/test_processor_seamless_m4t.py/0 | {
"file_path": "transformers/tests/models/seamless_m4t/test_processor_seamless_m4t.py",
"repo_id": "transformers",
"token_count": 2078
} | 468 |
# 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/table_transformer/test_modeling_table_transformer.py/0 | {
"file_path": "transformers/tests/models/table_transformer/test_modeling_table_transformer.py",
"repo_id": "transformers",
"token_count": 11586
} | 469 |
# coding=utf-8
# Copyright 2024 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/video_llava/test_image_processing_video_llava.py/0 | {
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# 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_flax_vision_text_dual_encoder.py/0 | {
"file_path": "transformers/tests/models/vision_text_dual_encoder/test_modeling_flax_vision_text_dual_encoder.py",
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"token_count": 6782
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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... | transformers/tests/models/wav2vec2/test_processor_wav2vec2.py/0 | {
"file_path": "transformers/tests/models/wav2vec2/test_processor_wav2vec2.py",
"repo_id": "transformers",
"token_count": 2550
} | 472 |
# 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_tf_whisper.py/0 | {
"file_path": "transformers/tests/models/whisper/test_modeling_tf_whisper.py",
"repo_id": "transformers",
"token_count": 21508
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# 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/xlm_roberta/test_modeling_flax_xlm_roberta.py/0 | {
"file_path": "transformers/tests/models/xlm_roberta/test_modeling_flax_xlm_roberta.py",
"repo_id": "transformers",
"token_count": 690
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# 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/yoso/test_modeling_yoso.py/0 | {
"file_path": "transformers/tests/models/yoso/test_modeling_yoso.py",
"repo_id": "transformers",
"token_count": 7167
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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... | transformers/tests/pipelines/test_pipelines_image_classification.py/0 | {
"file_path": "transformers/tests/pipelines/test_pipelines_image_classification.py",
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"token_count": 5466
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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... | transformers/tests/pipelines/test_pipelines_video_classification.py/0 | {
"file_path": "transformers/tests/pipelines/test_pipelines_video_classification.py",
"repo_id": "transformers",
"token_count": 1564
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# Testing new Hugging Face Deep Learning Container.
This document explains the testing strategy for releasing the new Hugging Face Deep Learning Container. AWS maintains 14 days of currency with framework releases. Besides framework releases, AWS release train is bi-weekly on Monday. Code cutoff date for any changes i... | transformers/tests/sagemaker/README.md/0 | {
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"token_count": 3293
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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/test_image_transforms.py/0 | {
"file_path": "transformers/tests/test_image_transforms.py",
"repo_id": "transformers",
"token_count": 12460
} | 479 |
# 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/trainer/test_trainer_seq2seq.py/0 | {
"file_path": "transformers/tests/trainer/test_trainer_seq2seq.py",
"repo_id": "transformers",
"token_count": 3782
} | 480 |
# 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/utils/test_dynamic_module_utils.py/0 | {
"file_path": "transformers/tests/utils/test_dynamic_module_utils.py",
"repo_id": "transformers",
"token_count": 918
} | 481 |
# 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/utils/test_offline.py/0 | {
"file_path": "transformers/tests/utils/test_offline.py",
"repo_id": "transformers",
"token_count": 2964
} | 482 |
# 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/utils/check_repo.py/0 | {
"file_path": "transformers/utils/check_repo.py",
"repo_id": "transformers",
"token_count": 19844
} | 483 |
# hello world experiment
python benchmark/benchmark.py \
--command "python examples/scripts/ppo.py --log_with wandb" \
--num-seeds 3 \
--start-seed 1 \
--workers 10 \
--slurm-nodes 1 \
--slurm-gpus-per-task 1 \
--slurm-ntasks 1 \
--slurm-total-cpus 12 \
--slurm-template-path benchmar... | trl/benchmark/benchmark_level1.sh/0 | {
"file_path": "trl/benchmark/benchmark_level1.sh",
"repo_id": "trl",
"token_count": 905
} | 484 |
# Aligning Text-to-Image Diffusion Models with Reward Backpropagation
## The why
If your reward function is differentiable, directly backpropagating gradients from the reward models to the diffusion model is significantly more sample and compute efficient (25x) than doing policy gradient algorithm like DDPO.
AlignPro... | trl/docs/source/alignprop_trainer.mdx/0 | {
"file_path": "trl/docs/source/alignprop_trainer.mdx",
"repo_id": "trl",
"token_count": 1505
} | 485 |
# KTO Trainer
TRL supports the Kahneman-Tversky Optimization (KTO) Trainer for aligning language models with binary feedback data (e.g., upvote/downvote), as described in the [paper](https://huggingface.co/papers/2402.01306) by Kawin Ethayarajh, Winnie Xu, Niklas Muennighoff, Dan Jurafsky, and Douwe Kiela.
For a full ... | trl/docs/source/kto_trainer.mdx/0 | {
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"repo_id": "trl",
"token_count": 1292
} | 486 |
# Trainer
At TRL we support PPO (Proximal Policy Optimisation) with an implementation that largely follows the structure introduced in the paper "Fine-Tuning Language Models from Human Preferences" by D. Ziegler et al. [[paper](https://huggingface.co/papers/1909.08593), [code](https://github.com/openai/lm-human-prefe... | trl/docs/source/trainer.mdx/0 | {
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"repo_id": "trl",
"token_count": 425
} | 487 |
# 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/tools/triviaqa.py/0 | {
"file_path": "trl/examples/research_projects/tools/triviaqa.py",
"repo_id": "trl",
"token_count": 2555
} | 488 |
# 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/scripts/ppo.py/0 | {
"file_path": "trl/examples/scripts/ppo.py",
"repo_id": "trl",
"token_count": 2796
} | 489 |
# 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... | trl/tests/test_environments.py/0 | {
"file_path": "trl/tests/test_environments.py",
"repo_id": "trl",
"token_count": 4797
} | 490 |
import unittest
import torch
from trl import is_peft_available
from trl.trainer.model_config import ModelConfig
from trl.trainer.utils import get_peft_config, pad
if is_peft_available():
from peft import LoraConfig
from .testing_utils import require_peft
class TestPad(unittest.TestCase):
def test_pad_1_d... | trl/tests/test_utils.py/0 | {
"file_path": "trl/tests/test_utils.py",
"repo_id": "trl",
"token_count": 1741
} | 491 |
# 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... | trl/trl/models/auxiliary_modules.py/0 | {
"file_path": "trl/trl/models/auxiliary_modules.py",
"repo_id": "trl",
"token_count": 1372
} | 492 |
# Copyright 2023 DDPO-pytorch authors (Kevin Black), metric-space, 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/lic... | trl/trl/trainer/ddpo_trainer.py/0 | {
"file_path": "trl/trl/trainer/ddpo_trainer.py",
"repo_id": "trl",
"token_count": 12357
} | 493 |
# 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/reward_config.py/0 | {
"file_path": "trl/trl/trainer/reward_config.py",
"repo_id": "trl",
"token_count": 551
} | 494 |
repos:
- repo: https://github.com/astral-sh/ruff-pre-commit
rev: v0.2.1
hooks:
- id: ruff
args:
- --fix
- id: ruff-format
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v4.5.0
hooks:
- id: check-merge-conflict
- id: check-yaml
| accelerate/.pre-commit-config.yaml/0 | {
"file_path": "accelerate/.pre-commit-config.yaml",
"repo_id": "accelerate",
"token_count": 158
} | 0 |
<!--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/concept_guides/big_model_inference.md/0 | {
"file_path": "accelerate/docs/source/concept_guides/big_model_inference.md",
"repo_id": "accelerate",
"token_count": 4832
} | 1 |
<!--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/usage_guides/distributed_inference.md/0 | {
"file_path": "accelerate/docs/source/usage_guides/distributed_inference.md",
"repo_id": "accelerate",
"token_count": 2940
} | 2 |
# What are these scripts?
All scripts in this folder originate from the `nlp_example.py` file, as it is a very simplistic NLP training example using Accelerate with zero extra features.
From there, each further script adds in just **one** feature of Accelerate, showing how you can quickly modify your own scripts to i... | accelerate/examples/by_feature/README.md/0 | {
"file_path": "accelerate/examples/by_feature/README.md",
"repo_id": "accelerate",
"token_count": 1692
} | 3 |
# Distributed inference examples
This folder contains a variety of tutorials for running distributed inference with the following strategy:
Load an entire model onto each GPU and sending chunks of a batch through each GPU’s model copy at a time
## Installation
```bash
pip install accelerate torch
```
## Running c... | accelerate/examples/inference/distributed/README.md/0 | {
"file_path": "accelerate/examples/inference/distributed/README.md",
"repo_id": "accelerate",
"token_count": 174
} | 4 |
# 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... | accelerate/src/accelerate/__init__.py/0 | {
"file_path": "accelerate/src/accelerate/__init__.py",
"repo_id": "accelerate",
"token_count": 500
} | 5 |
#!/usr/bin/env python
# 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
#
# Unles... | accelerate/src/accelerate/commands/launch.py/0 | {
"file_path": "accelerate/src/accelerate/commands/launch.py",
"repo_id": "accelerate",
"token_count": 19894
} | 6 |
# 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/logging.py/0 | {
"file_path": "accelerate/src/accelerate/logging.py",
"repo_id": "accelerate",
"token_count": 1842
} | 7 |
# 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/test_utils/scripts/test_ddp_comm_hook.py/0 | {
"file_path": "accelerate/src/accelerate/test_utils/scripts/test_ddp_comm_hook.py",
"repo_id": "accelerate",
"token_count": 1232
} | 8 |
# 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... | accelerate/src/accelerate/utils/fsdp_utils.py/0 | {
"file_path": "accelerate/src/accelerate/utils/fsdp_utils.py",
"repo_id": "accelerate",
"token_count": 6858
} | 9 |
{
"fp16": {
"enabled": "auto",
"loss_scale": 0,
"loss_scale_window": 1000,
"initial_scale_power": 16,
"hysteresis": 2,
"min_loss_scale": 1
},
"bf16": {
"enabled": "auto"
},
"optimizer": {
"type": "AdamW",
"params": {
... | accelerate/tests/deepspeed/ds_config_zero3.json/0 | {
"file_path": "accelerate/tests/deepspeed/ds_config_zero3.json",
"repo_id": "accelerate",
"token_count": 825
} | 10 |
# 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/test_examples.py/0 | {
"file_path": "accelerate/tests/test_examples.py",
"repo_id": "accelerate",
"token_count": 4720
} | 11 |
echo "hello world"
echo "this is a second command" | accelerate/tests/test_samples/test_command_file.sh/0 | {
"file_path": "accelerate/tests/test_samples/test_command_file.sh",
"repo_id": "accelerate",
"token_count": 14
} | 12 |
#!/bin/bash
# Define an array containing the base configs we wish to fine tune
configs=("zephyr" "openhermes")
# Define an array of loss types
loss_types=("sigmoid" "kto_pair" "ipo")
# Define an array of beta values
betas=("0.01" "0.1" "0.2" "0.3" "0.4" "0.5" "0.6" "0.7" "0.8" "0.9")
# Outer loop for loss types
for co... | alignment-handbook/recipes/pref_align_scan/launch_scan.sh/0 | {
"file_path": "alignment-handbook/recipes/pref_align_scan/launch_scan.sh",
"repo_id": "alignment-handbook",
"token_count": 430
} | 13 |
# Scripts to Train and Evaluate Chat Models
## Fine-tuning
In the handbook, we provide three main ways to align LLMs for chat:
- Full fine-tuning on a multi-GPU machine with DeepSpeed ZeRO-3 (tested on an 8 x A100 (80GB) node).
- LoRA or QLoRA fine-tuning on a single consumer 24GB GPU (tested on an RTX 4090).
- LoRA... | alignment-handbook/scripts/README.md/0 | {
"file_path": "alignment-handbook/scripts/README.md",
"repo_id": "alignment-handbook",
"token_count": 3136
} | 14 |
# 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... | alignment-handbook/tests/test_configs.py/0 | {
"file_path": "alignment-handbook/tests/test_configs.py",
"repo_id": "alignment-handbook",
"token_count": 697
} | 15 |
# candle
[](https://discord.gg/hugging-face-879548962464493619)
[](https://crates.io/crates/candle-core)
[](htt... | candle/README.md/0 | {
"file_path": "candle/README.md",
"repo_id": "candle",
"token_count": 8199
} | 16 |
# Pytorch cheatsheet
{{#include ../../../README.md:cheatsheet}}
| candle/candle-book/src/guide/cheatsheet.md/0 | {
"file_path": "candle/candle-book/src/guide/cheatsheet.md",
"repo_id": "candle",
"token_count": 26
} | 17 |
use crate::op::{BinaryOpT, CmpOp, ReduceOp, UnaryOpT};
use crate::{CpuStorage, DType, Layout, Result, Shape};
pub trait BackendStorage: Sized {
type Device: BackendDevice;
fn try_clone(&self, _: &Layout) -> Result<Self>;
fn dtype(&self) -> DType;
fn device(&self) -> &Self::Device;
// Maybe this... | candle/candle-core/src/backend.rs/0 | {
"file_path": "candle/candle-core/src/backend.rs",
"repo_id": "candle",
"token_count": 2111
} | 18 |
/// Helper functions to plug cuda kernels in candle.
use crate::{Layout, Result, Shape, WithDType};
pub use cudarc;
use cudarc::driver::{CudaSlice, DeviceRepr, ValidAsZeroBits};
use super::{CudaDevice, CudaError, WrapErr};
pub type S = super::CudaStorageSlice;
pub trait Map1 {
fn f<T: DeviceRepr + WithDType + Va... | candle/candle-core/src/cuda_backend/utils.rs/0 | {
"file_path": "candle/candle-core/src/cuda_backend/utils.rs",
"repo_id": "candle",
"token_count": 3748
} | 19 |
// Just enough pickle support to be able to read PyTorch checkpoints.
// This hardcodes objects that are required for tensor reading, we may want to make this a bit more
// composable/tensor agnostic at some point.
use crate::{DType, Error as E, Layout, Result, Tensor};
use byteorder::{LittleEndian, ReadBytesExt};
use ... | candle/candle-core/src/pickle.rs/0 | {
"file_path": "candle/candle-core/src/pickle.rs",
"repo_id": "candle",
"token_count": 14306
} | 20 |
use crate::{Result, Tensor};
use rayon::prelude::*;
#[derive(Debug, Clone, Copy)]
struct ArgSort {
asc: bool,
last_dim: usize,
}
impl ArgSort {
fn asort<T: crate::WithDType>(&self, vs: &[T], layout: &crate::Layout) -> Vec<u32> {
#[allow(clippy::uninit_vec)]
// Safety: indexes are set later... | candle/candle-core/src/sort.rs/0 | {
"file_path": "candle/candle-core/src/sort.rs",
"repo_id": "candle",
"token_count": 4817
} | 21 |
use candle_core::{test_device, DType, Device, IndexOp, Result, Tensor};
fn matmul(device: &Device) -> Result<()> {
let data = vec![1.0f32, 2.0, 3.0, 4.0];
let a = Tensor::from_slice(&data, (2, 2), device)?;
let data = vec![1.0f32, 2.0, 3.0, 4.0];
let b = Tensor::from_slice(&data, (2, 2), device)?;
... | candle/candle-core/tests/matmul_tests.rs/0 | {
"file_path": "candle/candle-core/tests/matmul_tests.rs",
"repo_id": "candle",
"token_count": 2363
} | 22 |
//! Datasets & Dataloaders for Candle
pub mod batcher;
pub mod hub;
pub mod nlp;
pub mod vision;
pub use batcher::Batcher;
| candle/candle-datasets/src/lib.rs/0 | {
"file_path": "candle/candle-datasets/src/lib.rs",
"repo_id": "candle",
"token_count": 45
} | 23 |
#[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::bigcode::{Config, GPTBigCode};
use candle::{DType, Device, Tensor};
use candle_nn::VarBuilder;
use candle_transformers:... | candle/candle-examples/examples/bigcode/main.rs/0 | {
"file_path": "candle/candle-examples/examples/bigcode/main.rs",
"repo_id": "candle",
"token_count": 2134
} | 24 |
use enterpolation::linear::ConstEquidistantLinear;
use enterpolation::Generator;
use palette::LinSrgb;
use candle::Tensor;
pub struct SpectralRColormap {
gradient: ConstEquidistantLinear<f32, LinSrgb, 9>,
}
impl SpectralRColormap {
pub(crate) fn new() -> Self {
// Define a colormap similar to 'Spectr... | candle/candle-examples/examples/depth_anything_v2/color_map.rs/0 | {
"file_path": "candle/candle-examples/examples/depth_anything_v2/color_map.rs",
"repo_id": "candle",
"token_count": 896
} | 25 |
//! EVA-02: Explore the limits of Visual representation at scAle
//! https://github.com/baaivision/EVA
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
use clap::Parser;
use candle::{DType, Device, IndexOp, Result, Tensor, D};
use candle_nn::{Module, Va... | candle/candle-examples/examples/eva2/main.rs/0 | {
"file_path": "candle/candle-examples/examples/eva2/main.rs",
"repo_id": "candle",
"token_count": 1221
} | 26 |
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
use clap::{Parser, ValueEnum};
use candle::{DType, IndexOp, D};
use candle_nn::{Module, VarBuilder};
use candle_transformers::models::hiera;
#[derive(Clone, Copy, Debug, ValueEnum)]
enum Which {
Tiny,... | candle/candle-examples/examples/hiera/main.rs/0 | {
"file_path": "candle/candle-examples/examples/hiera/main.rs",
"repo_id": "candle",
"token_count": 1257
} | 27 |
# candle-mamba: Mamba implementation
Candle implementation of *Mamba* [1] inference only. Mamba is an alternative to
the transformer architecture. It leverages State Space Models (SSMs) with the
goal of being computationally efficient on long sequences. The implementation is
based on [mamba.rs](https://github.com/Laur... | candle/candle-examples/examples/mamba/README.md/0 | {
"file_path": "candle/candle-examples/examples/mamba/README.md",
"repo_id": "candle",
"token_count": 190
} | 28 |
# candle-mobileone
[MobileOne: An Improved One millisecond Mobile Backbone](https://arxiv.org/abs/2206.04040).
This candle implementation uses a pre-trained MobileOne network for inference. The
classification head has been trained on the ImageNet dataset and returns the
probabilities for the top-5 classes.
## Runnin... | candle/candle-examples/examples/mobileone/README.md/0 | {
"file_path": "candle/candle-examples/examples/mobileone/README.md",
"repo_id": "candle",
"token_count": 254
} | 29 |
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
use clap::{Parser, ValueEnum};
use std::io::Write;
use tokenizers::Tokenizer;
use candle::quantized::gguf_file;
use candle::Tensor;
use candle_transformers::generation::{LogitsProcessor, Sampling};
use ca... | candle/candle-examples/examples/quantized-phi/main.rs/0 | {
"file_path": "candle/candle-examples/examples/quantized-phi/main.rs",
"repo_id": "candle",
"token_count": 5230
} | 30 |
#![allow(unused)]
//! Wrappers around the Python API of Gymnasium (the new version of OpenAI gym)
use candle::{Device, Result, Tensor};
use pyo3::prelude::*;
use pyo3::types::PyDict;
/// The return value for a step.
#[derive(Debug)]
pub struct Step<A> {
pub state: Tensor,
pub action: A,
pub reward: f64,
... | candle/candle-examples/examples/reinforcement-learning/gym_env.rs/0 | {
"file_path": "candle/candle-examples/examples/reinforcement-learning/gym_env.rs",
"repo_id": "candle",
"token_count": 1752
} | 31 |
# candle-segment-anything: Segment-Anything Model
This example is based on Meta AI [Segment-Anything
Model](https://github.com/facebookresearch/segment-anything). This model
provides a robust and fast image segmentation pipeline that can be tweaked via
some prompting (requesting some points to be in the target mask, r... | candle/candle-examples/examples/segment-anything/README.md/0 | {
"file_path": "candle/candle-examples/examples/segment-anything/README.md",
"repo_id": "candle",
"token_count": 573
} | 32 |
use symphonia::core::audio::{AudioBufferRef, Signal};
use symphonia::core::codecs::{DecoderOptions, CODEC_TYPE_NULL};
use symphonia::core::conv::FromSample;
fn conv<T>(samples: &mut Vec<f32>, data: std::borrow::Cow<symphonia::core::audio::AudioBuffer<T>>)
where
T: symphonia::core::sample::Sample,
f32: symphoni... | candle/candle-examples/examples/whisper/pcm_decode.rs/0 | {
"file_path": "candle/candle-examples/examples/whisper/pcm_decode.rs",
"repo_id": "candle",
"token_count": 1267
} | 33 |
#include "kernels.h"
#include "kernel_helpers.h"
#include "flash_fwd_launch_template.h"
void run_mha_fwd(Flash_fwd_params ¶ms, cudaStream_t stream) {
FP16_SWITCH(!params.is_bf16, [&] {
HEADDIM_SWITCH(params.d, [&] {
BOOL_SWITCH(params.is_causal, Is_causal, [&] {
run_mha_fwd_<elem_ty... | candle/candle-flash-attn/kernels/flash_api.cu/0 | {
"file_path": "candle/candle-flash-attn/kernels/flash_api.cu",
"repo_id": "candle",
"token_count": 1650
} | 34 |
[package]
name = "candle-kernels"
version = "0.6.1"
edition = "2021"
description = "CUDA kernels for Candle"
repository = "https://github.com/huggingface/candle"
keywords = ["blas", "tensor", "machine-learning"]
categories = ["science"]
license = "MIT OR Apache-2.0"
[dependencies]
[build-dependencies]
bindgen_cuda =... | candle/candle-kernels/Cargo.toml/0 | {
"file_path": "candle/candle-kernels/Cargo.toml",
"repo_id": "candle",
"token_count": 126
} | 35 |
#include "cuda_utils.cuh"
#include<stdint.h>
#define WHERE_OP(TYPENAME, ID_TYPENAME, FN_NAME) \
extern "C" __global__ void FN_NAME( \
const size_t numel, \
const size_t num_dims, \
const size_t *info, \
const ID_TYPENAME *ids, \
const TYPENAME *t, \
const TYPENAME *f, \
TYPENAME *out \
) ... | candle/candle-kernels/src/ternary.cu/0 | {
"file_path": "candle/candle-kernels/src/ternary.cu",
"repo_id": "candle",
"token_count": 1159
} | 36 |
use super::*;
use half::{bf16, f16};
use metal::MTLResourceOptions;
fn read_to_vec<T: Clone>(buffer: &Buffer, n: usize) -> Vec<T> {
let ptr = buffer.contents() as *const T;
assert!(!ptr.is_null());
let slice = unsafe { std::slice::from_raw_parts(ptr, n) };
slice.to_vec()
}
fn new_buffer<T>(device: &De... | candle/candle-metal-kernels/src/tests.rs/0 | {
"file_path": "candle/candle-metal-kernels/src/tests.rs",
"repo_id": "candle",
"token_count": 31494
} | 37 |
//! Batch Normalization.
//!
//! This layer applies Batch Normalization over a mini-batch of inputs as described in [`Batch
//! Normalization`]. The input is expected to have at least three dimensions.
//!
//! Note that this implementation is for inference only, there is no possibility to track the
//! running stats.
/... | candle/candle-nn/src/batch_norm.rs/0 | {
"file_path": "candle/candle-nn/src/batch_norm.rs",
"repo_id": "candle",
"token_count": 5325
} | 38 |
//! A sequential layer used to chain multiple layers and closures.
use candle::{Module, Result, Tensor};
/// A sequential layer combining multiple other layers.
pub struct Sequential {
layers: Vec<Box<dyn Module>>,
}
/// Creates a new empty sequential layer.
pub fn seq() -> Sequential {
Sequential { layers: v... | candle/candle-nn/src/sequential.rs/0 | {
"file_path": "candle/candle-nn/src/sequential.rs",
"repo_id": "candle",
"token_count": 705
} | 39 |
//
// WARNING: This file is automatically generated! Please edit onnx.in.proto.
//
// SPDX-License-Identifier: Apache-2.0
syntax = "proto3";
package onnx;
// Overview
//
// ONNX is an open specification that is comprised of the following components:
//
// 1) A definition of an extensible computation graph model... | candle/candle-onnx/src/onnx.proto3/0 | {
"file_path": "candle/candle-onnx/src/onnx.proto3",
"repo_id": "candle",
"token_count": 10183
} | 40 |
# Generated content DO NOT EDIT
from typing import Any, Callable, Dict, List, Optional, Tuple, Union, Sequence
from os import PathLike
from candle.typing import _ArrayLike, Device, Scalar, Index, Shape
from candle import Tensor, DType, QTensor
@staticmethod
def silu(tensor: Tensor) -> Tensor:
"""
Applies the S... | candle/candle-pyo3/py_src/candle/nn/__init__.pyi/0 | {
"file_path": "candle/candle-pyo3/py_src/candle/nn/__init__.pyi",
"repo_id": "candle",
"token_count": 181
} | 41 |
use ::candle::Tensor;
use pyo3::prelude::*;
#[derive(Clone, Debug)]
/// Represents an absolute shape e.g. (1, 2, 3)
pub struct PyShape(Vec<usize>);
impl<'source> pyo3::FromPyObject<'source> for PyShape {
fn extract(ob: &'source PyAny) -> PyResult<Self> {
if ob.is_none() {
return Err(PyErr::new... | candle/candle-pyo3/src/shape.rs/0 | {
"file_path": "candle/candle-pyo3/src/shape.rs",
"repo_id": "candle",
"token_count": 1646
} | 42 |
//! Based from the Stanford Hazy Research group.
//!
//! See "Simple linear attention language models balance the recall-throughput tradeoff", Arora et al. 2024
//! <https://arxiv.org/abs/2402.18668>
//! Original code:
//! https://github.com/HazyResearch/based
use candle::{DType, Device, IndexOp, Module, Result, Tens... | candle/candle-transformers/src/models/based.rs/0 | {
"file_path": "candle/candle-transformers/src/models/based.rs",
"repo_id": "candle",
"token_count": 9918
} | 43 |
use super::with_tracing::{linear, linear_no_bias, Embedding, Linear};
use candle::{DType, Device, IndexOp, Result, Tensor, D};
use candle_nn::{layer_norm, LayerNorm, Module, VarBuilder};
use serde::Deserialize;
pub const DTYPE: DType = DType::F32;
#[derive(Debug, Clone, Copy, PartialEq, Eq, Deserialize)]
#[serde(rena... | candle/candle-transformers/src/models/jina_bert.rs/0 | {
"file_path": "candle/candle-transformers/src/models/jina_bert.rs",
"repo_id": "candle",
"token_count": 6287
} | 44 |
// Implement the MMDiT model originally introduced for Stable Diffusion 3 (https://arxiv.org/abs/2403.03206).
// This follows the implementation of the MMDiT model in the ComfyUI repository.
// https://github.com/comfyanonymous/ComfyUI/blob/78e133d0415784924cd2674e2ee48f3eeca8a2aa/comfy/ldm/modules/diffusionmodules/mmd... | candle/candle-transformers/src/models/mmdit/model.rs/0 | {
"file_path": "candle/candle-transformers/src/models/mmdit/model.rs",
"repo_id": "candle",
"token_count": 2882
} | 45 |
use crate::models::with_tracing::{linear, linear_no_bias, Linear, RmsNorm};
use candle::{DType, Device, IndexOp, Module, Result, Tensor, D};
use candle_nn::{Activation, VarBuilder};
use std::sync::Arc;
#[derive(Debug, Clone, PartialEq, serde::Deserialize)]
pub struct Config {
pub vocab_size: usize,
pub hidden_... | candle/candle-transformers/src/models/qwen2.rs/0 | {
"file_path": "candle/candle-transformers/src/models/qwen2.rs",
"repo_id": "candle",
"token_count": 6708
} | 46 |
//! Contrastive Language-Image Pre-Training
//!
//! Contrastive Language-Image Pre-Training (CLIP) is an architecture trained on
//! pairs of images with related texts.
//!
//! https://github.com/openai/CLIP
use candle::{DType, Device, Result, Tensor, D};
use candle_nn as nn;
use candle_nn::Module;
#[derive(Debug, Clo... | candle/candle-transformers/src/models/stable_diffusion/clip.rs/0 | {
"file_path": "candle/candle-transformers/src/models/stable_diffusion/clip.rs",
"repo_id": "candle",
"token_count": 6474
} | 47 |
//! VGG-16 model implementation.
//!
//! See Very Deep Convolutional Networks for Large-Scale Image Recognition
//! <https://arxiv.org/abs/1409.1556>
use candle::{ModuleT, Result, Tensor};
use candle_nn::{FuncT, VarBuilder};
// Enum representing the different VGG models
pub enum Models {
Vgg13,
Vgg16,
Vgg1... | candle/candle-transformers/src/models/vgg.rs/0 | {
"file_path": "candle/candle-transformers/src/models/vgg.rs",
"repo_id": "candle",
"token_count": 4287
} | 48 |
pub mod text_generation;
| candle/candle-transformers/src/pipelines/mod.rs/0 | {
"file_path": "candle/candle-transformers/src/pipelines/mod.rs",
"repo_id": "candle",
"token_count": 7
} | 49 |
use yew_agent::PublicWorker;
fn main() {
console_error_panic_hook::set_once();
candle_wasm_example_llama2::Worker::register();
}
| candle/candle-wasm-examples/llama2-c/src/bin/worker.rs/0 | {
"file_path": "candle/candle-wasm-examples/llama2-c/src/bin/worker.rs",
"repo_id": "candle",
"token_count": 54
} | 50 |
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