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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/llava/test_processor_llava.py/0
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# coding=utf-8 # Copyright 2022 Tsimur Hadeliya. 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...
transformers/tests/models/longformer/test_tokenization_longformer.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/models/maskformer/test_image_processing_maskformer.py/0
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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/mgp_str/test_processor_mgp_str.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...
transformers/tests/models/mt5/test_modeling_flax_mt5.py/0
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# coding=utf-8 # Copyright 2024 HuggingFace Inc. team. All rights reserved. # Copyright (c) 2024, NVIDIA CORPORATION. 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/tests/models/nemotron/test_modeling_nemotron.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/models/owlv2/test_image_processing_owlv2.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/models/poolformer/test_image_processing_poolformer.py/0
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from __future__ import annotations import json import os import shutil import tempfile import unittest from unittest.mock import patch import numpy as np from transformers import BartTokenizer from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES as DPR_VOCAB_FILES_NAMES from transformers.models.d...
transformers/tests/models/rag/test_modeling_tf_rag.py/0
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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/sam/test_processor_sam.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/sew/test_modeling_sew.py/0
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# coding=utf-8 # Copyright 2021 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_speech_encoder_decoder.py/0
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# coding=utf-8 # Copyright 2020 The SqueezeBert 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/LICENSE-2.0 # # U...
transformers/tests/models/squeezebert/test_modeling_squeezebert.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/swin/test_modeling_swin.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/vit/test_modeling_vit.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/x_clip/test_modeling_x_clip.py/0
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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_xl/test_modeling_xlm_roberta_xl.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...
transformers/tests/pipelines/test_pipelines_image_feature_extraction.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...
transformers/tests/pipelines/test_pipelines_video_classification.py/0
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# coding=utf-8 # 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 requir...
transformers/tests/quantization/hqq/test_hqq.py/0
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519
import importlib def is_sagemaker_available(): return importlib.util.find_spec("sagemaker") is not None
transformers/tests/sagemaker/__init__.py/0
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520
# coding=utf-8 # Copyright 2019 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_modeling_common.py/0
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521
# 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_distributed.py/0
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522
# 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/utils/test_cache_utils.py/0
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import sys from transformers.utils.import_utils import clear_import_cache def test_clear_import_cache(): # Import some transformers modules # Get initial module count initial_modules = {name: mod for name, mod in sys.modules.items() if name.startswith("transformers.")} # Verify we have some modules...
transformers/tests/utils/test_import_utils.py/0
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524
#!/usr/bin/env python # 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/L...
transformers/utils/check_bad_commit.py/0
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525
# 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_tf_ops.py/0
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526
# 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/utils/notification_service.py/0
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527
# Detoxifying a Language Model using PPO Language models (LMs) are known to sometimes generate toxic outputs. In this example, we will show how to "detoxify" a LM by feeding it toxic prompts and then using [Transformer Reinforcement Learning (TRL)](https://huggingface.co/docs/trl/index) and Proximal Policy Optimizatio...
trl/docs/source/detoxifying_a_lm.md/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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529
# Copyright 2025 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/examples/datasets/rlaif-v.py/0
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530
# Copyright 2025 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/examples/research_projects/stack_llama_2/scripts/dpo_llama2.py/0
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# Copyright 2025 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/examples/scripts/evals/judge_tldr.py/0
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[tool.ruff] target-version = "py37" line-length = 119 [tool.ruff.lint] ignore = [ "B028", # warning without explicit stacklevel "C408", # dict() calls (stylistic) "C901", # function complexity "E501", ] extend-select = ["E", "F", "I", "W", "UP", "B", "T", "C"] [tool.ruff.lint.per-file-ignores] # Allow...
trl/pyproject.toml/0
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# Copyright 2025 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_best_of_n_sampler.py/0
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534
# Copyright 2025 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_judges.py/0
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535
# Copyright 2025 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_xpo_trainer.py/0
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536
# Copyright 2025 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/models/auxiliary_modules.py/0
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537
# Copyright 2025 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/alignprop_config.py/0
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538
# Copyright 2025 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/judges.py/0
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539
# Copyright 2025 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/rloo_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/big_model_inference/README.md/0
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# FP8 Benchmarks Comparing and running [TransformerEngine](https://github.com/NVIDIA/TransformerEngine) FP8 with accelerate ## Overview This repo provides scripts which compare native TransformerEngine model training against `accelerate`'s own integration. Each modeling type is segmented out via a script, supporting...
accelerate/benchmarks/fp8/transformer_engine/README.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/basic_tutorials/migration.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/index.md/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 applicable law or agreed...
accelerate/docs/source/quicktour.md/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 applicable law or agree...
accelerate/docs/source/usage_guides/profiler.md/0
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# Since this is single GPU, we don't need distributed training distributed_type: "NO" # Can be one of "no", "fp16", or "bf16" (see `transformer_engine.yaml` for `fp8`) mixed_precision: "bf16"
accelerate/examples/config_yaml_templates/single_gpu.yaml/0
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# 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 required by appl...
accelerate/examples/inference/pippy/llama.py/0
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7
# 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...
accelerate/manim_animations/dataloaders/stage_0.py/0
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#!/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/config/__init__.py/0
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9
# Copyright 2022 The HuggingFace Team and Brian Chao. 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...
accelerate/src/accelerate/commands/menu/selection_menu.py/0
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10
#!/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/test_utils/examples.py/0
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#!/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/test_utils/scripts/test_script.py/0
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12
# 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/memory.py/0
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13
# 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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14
# 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
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15
# Agent Course quiz scripts
agents-course/quiz/README.md/0
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16
# Actions: Enabling the Agent to Engage with Its Environment <Tip> In this section, we explore the concrete steps an AI agent takes to interact with its environment. We’ll cover how actions are represented (using JSON or code), the importance of the stop and parse approach, and introduce different types of agents...
agents-course/units/en/unit1/actions.mdx/0
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17
[package] name = "candle-book" 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 = { ...
candle/candle-book/Cargo.toml/0
{ "file_path": "candle/candle-book/Cargo.toml", "repo_id": "candle", "token_count": 459 }
18
# Installation **With Cuda support**: 1. First, make sure that Cuda is correctly installed. - `nvcc --version` should print information about your Cuda compiler driver. - `nvidia-smi --query-gpu=compute_cap --format=csv` should print your GPUs compute capability, e.g. something like: ```bash compute_cap 8.9 ``` You...
candle/candle-book/src/guide/installation.md/0
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mod benchmarks; use criterion::criterion_main; criterion_main!( benchmarks::affine::benches, benchmarks::matmul::benches, benchmarks::random::benches, benchmarks::reduce::benches, benchmarks::where_cond::benches, benchmarks::conv_transpose2d::benches, benchmarks::qmatmul::benches, benc...
candle/candle-core/benches/bench_main.rs/0
{ "file_path": "candle/candle-core/benches/bench_main.rs", "repo_id": "candle", "token_count": 126 }
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//! Methods for backpropagation of gradients. 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: &Ten...
candle/candle-core/src/backprop.rs/0
{ "file_path": "candle/candle-core/src/backprop.rs", "repo_id": "candle", "token_count": 24361 }
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use crate::op::{BackpropOp, Op}; use crate::tensor::from_storage; use crate::{CpuStorage, CudaStorage, Layout, MetalStorage, Result, Shape, Tensor}; use std::sync::Arc; /// Unary ops that can be defined in user-land. pub trait CustomOp1 { // Box<dyn> does not support const yet, so use a function to get the name. ...
candle/candle-core/src/custom_op.rs/0
{ "file_path": "candle/candle-core/src/custom_op.rs", "repo_id": "candle", "token_count": 7370 }
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use super::k_quants::{ BlockQ2K, BlockQ3K, BlockQ4K, BlockQ4_0, BlockQ5K, BlockQ6K, BlockQ8K, BlockQ8_0, QK8_0, QK_K, }; use crate::Result; use byteorder::{ByteOrder, LittleEndian}; use half::f16; #[cfg(target_arch = "x86")] use core::arch::x86::*; #[cfg(target_arch = "x86_64")] use core::arch::x86_64::*; #[inlin...
candle/candle-core/src/quantized/avx.rs/0
{ "file_path": "candle/candle-core/src/quantized/avx.rs", "repo_id": "candle", "token_count": 17495 }
23
use crate::backend::BackendStorage; use crate::op::{self, CmpOp, ReduceOp}; use crate::{CpuStorage, CudaStorage, DType, Device, Error, Layout, MetalStorage, Result, Shape}; use crate::{CustomOp1, CustomOp2, CustomOp3, InplaceOp1, InplaceOp2, InplaceOp3}; // We do not want to implement Clone on Storage as cloning may f...
candle/candle-core/src/storage.rs/0
{ "file_path": "candle/candle-core/src/storage.rs", "repo_id": "candle", "token_count": 15585 }
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import numpy as np x = np.arange(10) # Write a npy file. np.save("test.npy", x) # Write multiple values to a npz file. values = { "x": x, "x_plus_one": x + 1 } np.savez("test.npz", **values)
candle/candle-core/tests/npy.py/0
{ "file_path": "candle/candle-core/tests/npy.py", "repo_id": "candle", "token_count": 83 }
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pub mod tinystories;
candle/candle-datasets/src/nlp/mod.rs/0
{ "file_path": "candle/candle-datasets/src/nlp/mod.rs", "repo_id": "candle", "token_count": 6 }
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# candle-blip The [blip-image-captioning](https://huggingface.co/Salesforce/blip-image-captioning-base) model can generate captions for an input image. ## Running on an example ```bash cargo run --example blip --release -- --image candle-examples/examples/yolo-v8/assets/bike.jpg ``` ``` Running on CPU, to run on GP...
candle/candle-examples/examples/blip/README.md/0
{ "file_path": "candle/candle-examples/examples/blip/README.md", "repo_id": "candle", "token_count": 190 }
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// This example illustrates how to implement custom operations. These operations can provide their // own forward pass (CPU and GPU versions) as well as their backward pass. // // In this example we add the RMS normalization operation and implement it for f32. #[cfg(feature = "mkl")] extern crate intel_mkl_src; #[rus...
candle/candle-examples/examples/custom-ops/main.rs/0
{ "file_path": "candle/candle-examples/examples/custom-ops/main.rs", "repo_id": "candle", "token_count": 1475 }
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#[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::efficientvit; #[derive(Clone, Copy, Debug, ValueEnum)] enum Which { ...
candle/candle-examples/examples/efficientvit/main.rs/0
{ "file_path": "candle/candle-examples/examples/efficientvit/main.rs", "repo_id": "candle", "token_count": 1278 }
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// An implementation of LLaMA https://github.com/facebookresearch/llama // // This is based on nanoGPT in a similar way to: // https://github.com/Lightning-AI/lit-llama/blob/main/lit_llama/model.py // // The tokenizer config can be retrieved from: // https://huggingface.co/hf-internal-testing/llama-tokenizer/raw/main/t...
candle/candle-examples/examples/llama_multiprocess/main.rs/0
{ "file_path": "candle/candle-examples/examples/llama_multiprocess/main.rs", "repo_id": "candle", "token_count": 3774 }
30
#[cfg(feature = "mkl")] extern crate intel_mkl_src; #[cfg(feature = "accelerate")] extern crate accelerate_src; use anyhow::Result; use clap::Parser; use std::io::Write; use candle_transformers::generation::LogitsProcessor; use candle_transformers::models::encodec; use candle_transformers::models::metavoice::{adapte...
candle/candle-examples/examples/metavoice/main.rs/0
{ "file_path": "candle/candle-examples/examples/metavoice/main.rs", "repo_id": "candle", "token_count": 4560 }
31
use std::path::PathBuf; use anyhow::{Error as E, Result}; use candle::{Device, Tensor}; use candle_nn::VarBuilder; use candle_transformers::models::modernbert; use clap::{Parser, ValueEnum}; use hf_hub::{api::sync::Api, Repo, RepoType}; use tokenizers::{PaddingParams, Tokenizer}; #[derive(Debug, Clone, ValueEnum)] en...
candle/candle-examples/examples/modernbert/main.rs/0
{ "file_path": "candle/candle-examples/examples/modernbert/main.rs", "repo_id": "candle", "token_count": 2425 }
32
#[cfg(feature = "mkl")] extern crate intel_mkl_src; #[cfg(feature = "accelerate")] extern crate accelerate_src; use anyhow::Error as E; use clap::Parser; use candle::{DType, IndexOp, Tensor}; use candle_nn::VarBuilder; use candle_transformers::models::parler_tts::{Config, Model}; use tokenizers::Tokenizer; #[derive...
candle/candle-examples/examples/parler-tts/main.rs/0
{ "file_path": "candle/candle-examples/examples/parler-tts/main.rs", "repo_id": "candle", "token_count": 2678 }
33
## 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
{ "file_path": "candle/candle-examples/examples/rwkv/README.md", "repo_id": "candle", "token_count": 235 }
34
# candle-stable-diffusion-3: Candle Implementation of Stable Diffusion 3/3.5 ![](assets/stable-diffusion-3.jpg) *A cute rusty robot holding a candle torch in its hand, with glowing neon text \"LETS GO RUSTY\" displayed on its chest, bright background, high quality, 4k*, generated by Stable Diffusion 3 Medium Stable ...
candle/candle-examples/examples/stable-diffusion-3/README.md/0
{ "file_path": "candle/candle-examples/examples/stable-diffusion-3/README.md", "repo_id": "candle", "token_count": 1343 }
35
use candle::{IndexOp, Result, Tensor, D}; use tokenizers::Tokenizer; const LANGUAGES: [(&str, &str); 99] = [ ("en", "english"), ("zh", "chinese"), ("de", "german"), ("es", "spanish"), ("ru", "russian"), ("ko", "korean"), ("fr", "french"), ("ja", "japanese"), ("pt", "portuguese"), ...
candle/candle-examples/examples/whisper/multilingual.rs/0
{ "file_path": "candle/candle-examples/examples/whisper/multilingual.rs", "repo_id": "candle", "token_count": 1846 }
36
/****************************************************************************** * Copyright (c) 2024, Tri Dao. ******************************************************************************/ #pragma once #include "philox.cuh" #include "utils.h" namespace flash { struct Dropout { const unsigned long long seed...
candle/candle-flash-attn/kernels/dropout.h/0
{ "file_path": "candle/candle-flash-attn/kernels/dropout.h", "repo_id": "candle", "token_count": 3021 }
37
/****************************************************************************** * Copyright (c) 2023, Tri Dao. ******************************************************************************/ #pragma once #include <assert.h> #include <stdint.h> #include <stdlib.h> #include <cuda_fp16.h> #if defined(__CUDA_ARCH__) ...
candle/candle-flash-attn/kernels/utils.h/0
{ "file_path": "candle/candle-flash-attn/kernels/utils.h", "repo_id": "candle", "token_count": 8100 }
38
pub const AFFINE: &str = include_str!(concat!(env!("OUT_DIR"), "/affine.ptx")); pub const BINARY: &str = include_str!(concat!(env!("OUT_DIR"), "/binary.ptx")); pub const CAST: &str = include_str!(concat!(env!("OUT_DIR"), "/cast.ptx")); pub const CONV: &str = include_str!(concat!(env!("OUT_DIR"), "/conv.ptx")); pub cons...
candle/candle-kernels/src/lib.rs/0
{ "file_path": "candle/candle-kernels/src/lib.rs", "repo_id": "candle", "token_count": 365 }
39
// MLX Kernel extracted from: // https://github.com/ml-explore/mlx/blob/main/mlx/backend/metal/kernels/steel/gemm // Copyright © 2024 Apple Inc. #include <metal_simdgroup> #include <metal_simdgroup_matrix> #include <metal_stdlib> #define STEEL_CONST static constant constexpr const #define STEEL_PRAGMA_UNROLL _Pragma(...
candle/candle-metal-kernels/src/mlx_gemm.metal/0
{ "file_path": "candle/candle-metal-kernels/src/mlx_gemm.metal", "repo_id": "candle", "token_count": 20231 }
40
use candle_metal_kernels::{call_cast_contiguous, Kernels}; use metal::objc::rc::autoreleasepool; use metal::{Device, MTLResourceOptions}; use rand; use std::any::type_name; use std::time::Instant; fn main() { let device = Device::system_default().unwrap(); let kernels = Kernels::new(); let f32_1k = (0..10...
candle/candle-metal-kernels/tmp/cast.rs/0
{ "file_path": "candle/candle-metal-kernels/tmp/cast.rs", "repo_id": "candle", "token_count": 1299 }
41
//! Layers defined by closures. use candle::{Result, Tensor}; use std::sync::Arc; /// A layer defined by a simple closure. #[derive(Clone)] pub struct Func<'a> { #[allow(clippy::type_complexity)] f: Arc<dyn 'a + Fn(&Tensor) -> Result<Tensor> + Send + Sync>, } impl std::fmt::Debug for Func<'_> { fn fmt(&se...
candle/candle-nn/src/func.rs/0
{ "file_path": "candle/candle-nn/src/func.rs", "repo_id": "candle", "token_count": 784 }
42
/* Equivalent PyTorch code. import torch from torch.nn.functional import group_norm t = torch.tensor( [[[-0.3034, 0.2726, -0.9659], [-1.1845, -1.3236, 0.0172], [ 1.9507, 1.2554, -0.8625], [ 1.0682, 0.3604, 0.3985], [-0.4957, -0.4461, -0.9721], [ 1.5157, -0....
candle/candle-nn/tests/group_norm.rs/0
{ "file_path": "candle/candle-nn/tests/group_norm.rs", "repo_id": "candle", "token_count": 2154 }
43
import math from typing import Any import candle from candle import Tensor from .module import Module # See https://github.com/pytorch/pytorch/blob/main/torch/nn/modules/linear.py class Identity(Module): r"""A placeholder identity operator that is argument-insensitive. Args: args: any argument (unu...
candle/candle-pyo3/py_src/candle/nn/linear.py/0
{ "file_path": "candle/candle-pyo3/py_src/candle/nn/linear.py", "repo_id": "candle", "token_count": 1947 }
44
# See: https://raw.githubusercontent.com/huggingface/tokenizers/main/bindings/python/stub.py import argparse import inspect import os from typing import Optional import black from pathlib import Path import re INDENT = " " * 4 GENERATED_COMMENT = "# Generated content DO NOT EDIT\n" TYPING = """from typing import Any,...
candle/candle-pyo3/stub.py/0
{ "file_path": "candle/candle-pyo3/stub.py", "repo_id": "candle", "token_count": 3931 }
45
//! BERT (Bidirectional Encoder Representations from Transformers) //! //! Bert is a general large language model that can be used for various language tasks: //! - Compute sentence embeddings for a prompt. //! - Compute similarities between a set of sentences. //! - [Arxiv](https://arxiv.org/abs/1810.04805) "BERT: Pre...
candle/candle-transformers/src/models/bert.rs/0
{ "file_path": "candle/candle-transformers/src/models/bert.rs", "repo_id": "candle", "token_count": 10056 }
46
use std::collections::HashMap; use candle::{bail, Context, DType, Device, Module, Result, Tensor, D}; use candle_nn::{ conv1d, embedding, layer_norm, Conv1d, Conv1dConfig, Embedding, LayerNorm, VarBuilder, }; use serde::{Deserialize, Deserializer}; pub const DTYPE: DType = DType::F32; // NOTE: HiddenAct and Hidd...
candle/candle-transformers/src/models/debertav2.rs/0
{ "file_path": "candle/candle-transformers/src/models/debertav2.rs", "repo_id": "candle", "token_count": 24495 }
47
use candle::{Device, Result, Tensor}; pub fn get_noise( num_samples: usize, height: usize, width: usize, device: &Device, ) -> Result<Tensor> { let height = (height + 15) / 16 * 2; let width = (width + 15) / 16 * 2; Tensor::randn(0f32, 1., (num_samples, 16, height, width), device) } #[deri...
candle/candle-transformers/src/models/flux/sampling.rs/0
{ "file_path": "candle/candle-transformers/src/models/flux/sampling.rs", "repo_id": "candle", "token_count": 2063 }
48
//! MetaVoice Studio ML Models //! //! See MetaVoice's TTS and voice cloning models: //! - [Github](https://github.com/metavoiceio/metavoice-src) //! - [Website](https://studio.metavoice.ai/) use candle::{DType, Device, Error as E, IndexOp, Module, Result, Tensor, D}; use candle_nn::{embedding, linear_b, rms_norm, Emb...
candle/candle-transformers/src/models/metavoice.rs/0
{ "file_path": "candle/candle-transformers/src/models/metavoice.rs", "repo_id": "candle", "token_count": 21763 }
49
//! # MobileNet-v4 //! //! MobileNet-v4 inference implementation based on timm. //! //! ## Paper //! //! ["MobileNetV4 - Universal Models for the Mobile Ecosystem"](https://arxiv.org/abs/2404.10518) //! //! ## References //! //! - [PyTorch Implementation](https://github.com/huggingface/pytorch-image-models/blob/main/ti...
candle/candle-transformers/src/models/mobilenetv4.rs/0
{ "file_path": "candle/candle-transformers/src/models/mobilenetv4.rs", "repo_id": "candle", "token_count": 16908 }
50
//! Microsoft Phi-3 model implementation //! //! See Phi model details at: //! - [Phi-3 Model](https://huggingface.co/microsoft/phi-3) //! //! The Phi series are decoder-only transformers designed for code and language tasks. //! Key characteristics: //! - Decoder-only transformer architecture //! - RoPE embeddings //!...
candle/candle-transformers/src/models/phi3.rs/0
{ "file_path": "candle/candle-transformers/src/models/phi3.rs", "repo_id": "candle", "token_count": 5916 }
51
//! Recurrent Gemma model implementation with quantization support. //! //! Gemma is a large language model optimized for efficiency. //! This implementation provides quantization for reduced memory and compute. //! //! Key characteristics: //! - Recurrent blocks with gated recurrent units //! - Convolution and attenti...
candle/candle-transformers/src/models/quantized_recurrent_gemma.rs/0
{ "file_path": "candle/candle-transformers/src/models/quantized_recurrent_gemma.rs", "repo_id": "candle", "token_count": 7858 }
52
use candle::{DType, IndexOp, Result, Tensor, D}; use candle_nn::VarBuilder; #[derive(Debug)] struct PositionEmbeddingRandom { positional_encoding_gaussian_matrix: Tensor, } impl PositionEmbeddingRandom { fn new(num_pos_feats: usize, vb: VarBuilder) -> Result<Self> { let positional_encoding_gaussian_ma...
candle/candle-transformers/src/models/segment_anything/prompt_encoder.rs/0
{ "file_path": "candle/candle-transformers/src/models/segment_anything/prompt_encoder.rs", "repo_id": "candle", "token_count": 4745 }
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//! # UniPC Scheduler //! //! UniPC is a training-free framework designed for the fast sampling of diffusion models, which consists of a //! corrector (UniC) and a predictor (UniP) that share a unified analytical form and support arbitrary orders. //! //! UniPC is by design model-agnostic, supporting pixel-space/latent...
candle/candle-transformers/src/models/stable_diffusion/uni_pc.rs/0
{ "file_path": "candle/candle-transformers/src/models/stable_diffusion/uni_pc.rs", "repo_id": "candle", "token_count": 17600 }
54
use candle::{DType, Module, Result, Tensor, D}; use candle_nn::VarBuilder; // https://github.com/huggingface/diffusers/blob/19edca82f1ff194c07317369a92b470dbae97f34/src/diffusers/pipelines/wuerstchen/modeling_wuerstchen_common.py#L22 #[derive(Debug)] pub struct WLayerNorm { eps: f64, } impl WLayerNorm { pub f...
candle/candle-transformers/src/models/wuerstchen/common.rs/0
{ "file_path": "candle/candle-transformers/src/models/wuerstchen/common.rs", "repo_id": "candle", "token_count": 3219 }
55
[package] name = "candle-wasm-example-bert" version.workspace = true edition.workspace = true description.workspace = true repository.workspace = true keywords.workspace = true categories.workspace = true license.workspace = true [dependencies] candle = { workspace = true } candle-nn = { workspace = true } candle-tran...
candle/candle-wasm-examples/bert/Cargo.toml/0
{ "file_path": "candle/candle-wasm-examples/bert/Cargo.toml", "repo_id": "candle", "token_count": 304 }
56
[package] name = "candle-wasm-example-llama2" version.workspace = true edition.workspace = true description.workspace = true repository.workspace = true keywords.workspace = true categories.workspace = true license.workspace = true [dependencies] candle = { workspace = true } candle-nn = { workspace = true } candle-tr...
candle/candle-wasm-examples/llama2-c/Cargo.toml/0
{ "file_path": "candle/candle-wasm-examples/llama2-c/Cargo.toml", "repo_id": "candle", "token_count": 434 }
57
import snarkdown from "https://cdn.skypack.dev/snarkdown"; import hljs from "https://cdn.skypack.dev/highlight.js"; // models base url const MODELS = { moondream2_q4k: { base_url: "https://huggingface.co/santiagomed/candle-moondream/resolve/main/", model: "model-q4_0.gguf", tokenizer: "tokenizer.jso...
candle/candle-wasm-examples/moondream/code.js/0
{ "file_path": "candle/candle-wasm-examples/moondream/code.js", "repo_id": "candle", "token_count": 2873 }
58