text stringlengths 5 409k | id stringlengths 14 178 | metadata dict | __index_level_0__ int64 0 572 |
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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/mobilevit/test_image_processing_mobilevit.py/0 | {
"file_path": "transformers/tests/models/mobilevit/test_image_processing_mobilevit.py",
"repo_id": "transformers",
"token_count": 4049
} | 527 |
# 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 | {
"file_path": "transformers/tests/models/mvp/test_modeling_mvp.py",
"repo_id": "transformers",
"token_count": 15199
} | 528 |
# 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/olmo/test_modeling_olmo.py/0 | {
"file_path": "transformers/tests/models/olmo/test_modeling_olmo.py",
"repo_id": "transformers",
"token_count": 9772
} | 529 |
# coding=utf-8
# Copyright 2025 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/paligemma2/test_modeling_paligemma2.py/0 | {
"file_path": "transformers/tests/models/paligemma2/test_modeling_paligemma2.py",
"repo_id": "transformers",
"token_count": 6268
} | 530 |
# 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/persimmon/test_modeling_persimmon.py/0 | {
"file_path": "transformers/tests/models/persimmon/test_modeling_persimmon.py",
"repo_id": "transformers",
"token_count": 10275
} | 531 |
# 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/models/pixtral/test_processor_pixtral.py/0 | {
"file_path": "transformers/tests/models/pixtral/test_processor_pixtral.py",
"repo_id": "transformers",
"token_count": 6179
} | 532 |
# 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/pvt/test_image_processing_pvt.py/0 | {
"file_path": "transformers/tests/models/pvt/test_image_processing_pvt.py",
"repo_id": "transformers",
"token_count": 1533
} | 533 |
# 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/qwen2_vl/test_image_processing_qwen2_vl.py/0 | {
"file_path": "transformers/tests/models/qwen2_vl/test_image_processing_qwen2_vl.py",
"repo_id": "transformers",
"token_count": 6659
} | 534 |
# 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/regnet/test_modeling_tf_regnet.py/0 | {
"file_path": "transformers/tests/models/regnet/test_modeling_tf_regnet.py",
"repo_id": "transformers",
"token_count": 4801
} | 535 |
# 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/roberta_prelayernorm/test_modeling_roberta_prelayernorm.py/0 | {
"file_path": "transformers/tests/models/roberta_prelayernorm/test_modeling_roberta_prelayernorm.py",
"repo_id": "transformers",
"token_count": 10532
} | 536 |
# 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/segformer/test_modeling_tf_segformer.py/0 | {
"file_path": "transformers/tests/models/segformer/test_modeling_tf_segformer.py",
"repo_id": "transformers",
"token_count": 9719
} | 537 |
# 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/smolvlm/test_image_processing_smolvlm.py/0 | {
"file_path": "transformers/tests/models/smolvlm/test_image_processing_smolvlm.py",
"repo_id": "transformers",
"token_count": 5413
} | 538 |
# 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/models/superpoint/test_modeling_superpoint.py/0 | {
"file_path": "transformers/tests/models/superpoint/test_modeling_superpoint.py",
"repo_id": "transformers",
"token_count": 5398
} | 539 |
# coding=utf-8
# Copyright 2018 Google T5 Authors and HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requ... | transformers/tests/models/t5/test_modeling_t5.py/0 | {
"file_path": "transformers/tests/models/t5/test_modeling_t5.py",
"repo_id": "transformers",
"token_count": 36620
} | 540 |
# 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/umt5/test_modeling_umt5.py/0 | {
"file_path": "transformers/tests/models/umt5/test_modeling_umt5.py",
"repo_id": "transformers",
"token_count": 16365
} | 541 |
# 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/visual_bert/test_modeling_visual_bert.py/0 | {
"file_path": "transformers/tests/models/visual_bert/test_modeling_visual_bert.py",
"repo_id": "transformers",
"token_count": 14015
} | 542 |
# 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": 2924
} | 543 |
# 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": 18045
} | 544 |
# 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
} | 545 |
# 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": 7171
} | 546 |
# 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_depth_estimation.py/0 | {
"file_path": "transformers/tests/pipelines/test_pipelines_depth_estimation.py",
"repo_id": "transformers",
"token_count": 2445
} | 547 |
# Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | transformers/tests/pipelines/test_pipelines_text_classification.py/0 | {
"file_path": "transformers/tests/pipelines/test_pipelines_text_classification.py",
"repo_id": "transformers",
"token_count": 4424
} | 548 |
# 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/bitnet_integration/test_bitnet.py/0 | {
"file_path": "transformers/tests/quantization/bitnet_integration/test_bitnet.py",
"repo_id": "transformers",
"token_count": 3339
} | 549 |
# 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/ggml/test_ggml.py/0 | {
"file_path": "transformers/tests/quantization/ggml/test_ggml.py",
"repo_id": "transformers",
"token_count": 19171
} | 550 |
# 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/repo_utils/test_check_docstrings.py/0 | {
"file_path": "transformers/tests/repo_utils/test_check_docstrings.py",
"repo_id": "transformers",
"token_count": 1935
} | 551 |
# 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/test_backbone_common.py/0 | {
"file_path": "transformers/tests/test_backbone_common.py",
"repo_id": "transformers",
"token_count": 4375
} | 552 |
# 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/tp/test_tp.py/0 | {
"file_path": "transformers/tests/tp/test_tp.py",
"repo_id": "transformers",
"token_count": 2641
} | 553 |
# 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_activations.py/0 | {
"file_path": "transformers/tests/utils/test_activations.py",
"repo_id": "transformers",
"token_count": 1055
} | 554 |
# 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_hf_argparser.py/0 | {
"file_path": "transformers/tests/utils/test_hf_argparser.py",
"repo_id": "transformers",
"token_count": 7886
} | 555 |
# coding=utf-8
# Copyright 2019-present, 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 a... | transformers/tests/utils/test_skip_decorators.py/0 | {
"file_path": "transformers/tests/utils/test_skip_decorators.py",
"repo_id": "transformers",
"token_count": 1214
} | 556 |
import argparse
import difflib
import glob
import logging
import subprocess
from io import StringIO
from create_dependency_mapping import find_priority_list
# Console for rich printing
from modular_model_converter import convert_modular_file
from rich.console import Console
from rich.syntax import Syntax
logging.ba... | transformers/utils/check_modular_conversion.py/0 | {
"file_path": "transformers/utils/check_modular_conversion.py",
"repo_id": "transformers",
"token_count": 2816
} | 557 |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable... | transformers/utils/get_test_info.py/0 | {
"file_path": "transformers/utils/get_test_info.py",
"repo_id": "transformers",
"token_count": 2737
} | 558 |
"""A simple script to set flexibly CUDA_VISIBLE_DEVICES in GitHub Actions CI workflow files."""
import argparse
import os
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument(
"--test_folder",
type=str,
default=None,
help="The test folder name of t... | transformers/utils/set_cuda_devices_for_ci.py/0 | {
"file_path": "transformers/utils/set_cuda_devices_for_ci.py",
"repo_id": "transformers",
"token_count": 338
} | 559 |
# coding=utf-8
# Copyright 2021 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable... | transformers/utils/update_metadata.py/0 | {
"file_path": "transformers/utils/update_metadata.py",
"repo_id": "transformers",
"token_count": 6448
} | 560 |
# Training customization
TRL is designed with modularity in mind so that users to be able to efficiently customize the training loop for their needs. Below are some examples on how you can apply and test different techniques. Note: Although these examples use the DPOTrainer, the customization applies to most (if not ... | trl/docs/source/customization.md/0 | {
"file_path": "trl/docs/source/customization.md",
"repo_id": "trl",
"token_count": 2231
} | 561 |
# Learning Tools (Experimental 🧪)
Using Large Language Models (LLMs) with tools has been a popular topic recently with awesome works such as [ToolFormer](https://huggingface.co/papers/2302.04761) and [ToolBench](https://huggingface.co/papers/2305.16504). In TRL, we provide a simple example of how to teach LLM to use ... | trl/docs/source/learning_tools.md/0 | {
"file_path": "trl/docs/source/learning_tools.md",
"repo_id": "trl",
"token_count": 3870
} | 562 |
# Sentiment Tuning Examples
The notebooks and scripts in this examples show how to fine-tune a model with a sentiment classifier (such as `lvwerra/distilbert-imdb`).
Here's an overview of the notebooks and scripts in the [trl repository](https://github.com/huggingface/trl/tree/main/examples):
| File ... | trl/docs/source/sentiment_tuning.md/0 | {
"file_path": "trl/docs/source/sentiment_tuning.md",
"repo_id": "trl",
"token_count": 1080
} | 563 |
# 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/hh-rlhf-helpful-base.py/0 | {
"file_path": "trl/examples/datasets/hh-rlhf-helpful-base.py",
"repo_id": "trl",
"token_count": 1843
} | 564 |
# 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/scripts/merge_peft_adapter.py/0 | {
"file_path": "trl/examples/research_projects/stack_llama/scripts/merge_peft_adapter.py",
"repo_id": "trl",
"token_count": 814
} | 565 |
# 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/cpo.py/0 | {
"file_path": "trl/examples/scripts/cpo.py",
"repo_id": "trl",
"token_count": 1338
} | 566 |
# 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/slow/test_dpo_slow.py/0 | {
"file_path": "trl/tests/slow/test_dpo_slow.py",
"repo_id": "trl",
"token_count": 4082
} | 567 |
# 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_dpo_trainer.py/0 | {
"file_path": "trl/tests/test_dpo_trainer.py",
"repo_id": "trl",
"token_count": 27028
} | 568 |
# 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/extras/dataset_formatting.py/0 | {
"file_path": "trl/trl/extras/dataset_formatting.py",
"repo_id": "trl",
"token_count": 1642
} | 569 |
# 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/scripts/kto.py/0 | {
"file_path": "trl/trl/scripts/kto.py",
"repo_id": "trl",
"token_count": 1619
} | 570 |
# 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/gkd_config.py/0 | {
"file_path": "trl/trl/trainer/gkd_config.py",
"repo_id": "trl",
"token_count": 1765
} | 571 |
# 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/ppo_trainer.py/0 | {
"file_path": "trl/trl/trainer/ppo_trainer.py",
"repo_id": "trl",
"token_count": 19228
} | 572 |
FROM ghcr.io/azure/msamp
RUN pip install transformers evaluate datasets
RUN git clone https://github.com/huggingface/accelerate
RUN cd accelerate && \
pip install -e . && \
cd benchmarks/fp8
CMD ["bash"]
| accelerate/benchmarks/fp8/ms_amp/Dockerfile/0 | {
"file_path": "accelerate/benchmarks/fp8/ms_amp/Dockerfile",
"repo_id": "accelerate",
"token_count": 78
} | 0 |
<!--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 agreed... | accelerate/docs/source/basic_tutorials/tpu.md/0 | {
"file_path": "accelerate/docs/source/basic_tutorials/tpu.md",
"repo_id": "accelerate",
"token_count": 629
} | 1 |
<!--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/package_reference/cli.md/0 | {
"file_path": "accelerate/docs/source/package_reference/cli.md",
"repo_id": "accelerate",
"token_count": 5968
} | 2 |
<!--
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 agree... | accelerate/docs/source/usage_guides/ddp_comm_hook.md/0 | {
"file_path": "accelerate/docs/source/usage_guides/ddp_comm_hook.md",
"repo_id": "accelerate",
"token_count": 3366
} | 3 |
<!--Copyright 2022 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | accelerate/docs/source/usage_guides/tracking.md/0 | {
"file_path": "accelerate/docs/source/usage_guides/tracking.md",
"repo_id": "accelerate",
"token_count": 2703
} | 4 |
# 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/examples/multigpu_remote_launcher.py/0 | {
"file_path": "accelerate/examples/multigpu_remote_launcher.py",
"repo_id": "accelerate",
"token_count": 1026
} | 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/config/config_args.py/0 | {
"file_path": "accelerate/src/accelerate/commands/config/config_args.py",
"repo_id": "accelerate",
"token_count": 4284
} | 6 |
#!/usr/bin/env python
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unles... | accelerate/src/accelerate/commands/tpu.py/0 | {
"file_path": "accelerate/src/accelerate/commands/tpu.py",
"repo_id": "accelerate",
"token_count": 2114
} | 7 |
# 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 required by appl... | accelerate/src/accelerate/test_utils/scripts/external_deps/test_checkpointing.py/0 | {
"file_path": "accelerate/src/accelerate/test_utils/scripts/external_deps/test_checkpointing.py",
"repo_id": "accelerate",
"token_count": 4199
} | 8 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate/src/accelerate/test_utils/training.py/0 | {
"file_path": "accelerate/src/accelerate/test_utils/training.py",
"repo_id": "accelerate",
"token_count": 2582
} | 9 |
# 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/operations.py/0 | {
"file_path": "accelerate/src/accelerate/utils/operations.py",
"repo_id": "accelerate",
"token_count": 12875
} | 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_accelerator.py/0 | {
"file_path": "accelerate/tests/test_accelerator.py",
"repo_id": "accelerate",
"token_count": 15183
} | 11 |
# 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_hooks.py/0 | {
"file_path": "accelerate/tests/test_hooks.py",
"repo_id": "accelerate",
"token_count": 6577
} | 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/tests/test_state_checkpointing.py/0 | {
"file_path": "accelerate/tests/test_state_checkpointing.py",
"repo_id": "accelerate",
"token_count": 8971
} | 13 |
[project]
name = "agents-course"
version = "0.1.0"
description = "Add your description here"
readme = "README.md"
requires-python = ">=3.11"
dependencies = [
"datasets>=3.2.0",
"huggingface-hub>=0.27.1",
"ipykernel>=6.29.5",
"requests>=2.32.3",
]
| agents-course/quiz/pyproject.toml/0 | {
"file_path": "agents-course/quiz/pyproject.toml",
"repo_id": "agents-course",
"token_count": 126
} | 14 |
# Dummy Agent Library
<img src="https://huggingface.co/datasets/agents-course/course-images/resolve/main/en/unit1/whiteboard-unit1sub3DONE.jpg" alt="Unit 1 planning"/>
This course is framework-agnostic because we want to **focus on the concepts of AI agents and avoid getting bogged down in the specifics of a particul... | agents-course/units/en/unit1/dummy-agent-library.mdx/0 | {
"file_path": "agents-course/units/en/unit1/dummy-agent-library.mdx",
"repo_id": "agents-course",
"token_count": 3522
} | 15 |
# Summary
[Introduction](README.md)
# User Guide
- [Installation](guide/installation.md)
- [Hello World - MNIST](guide/hello_world.md)
- [PyTorch cheatsheet](guide/cheatsheet.md)
# Reference Guide
- [Running a model](inference/inference.md)
- [Using the hub](inference/hub.md)
- [Error management](error_manage.... | candle/candle-book/src/SUMMARY.md/0 | {
"file_path": "candle/candle-book/src/SUMMARY.md",
"repo_id": "candle",
"token_count": 274
} | 16 |
# Writing a custom kernel
| candle/candle-book/src/inference/cuda/writing.md/0 | {
"file_path": "candle/candle-book/src/inference/cuda/writing.md",
"repo_id": "candle",
"token_count": 6
} | 17 |
use crate::benchmarks::{BenchDevice, BenchDeviceHandler};
use candle_core::{DType, Device, Tensor};
use criterion::{black_box, criterion_group, Criterion, Throughput};
use std::time::Instant;
fn run(a: &Tensor, b: &Tensor) {
a.matmul(&b.t().unwrap()).unwrap();
}
fn run_bench(c: &mut Criterion, device: &Device) {
... | candle/candle-core/benches/benchmarks/matmul.rs/0 | {
"file_path": "candle/candle-core/benches/benchmarks/matmul.rs",
"repo_id": "candle",
"token_count": 551
} | 18 |
use super::{Cpu, CpuF16};
#[cfg(target_arch = "x86")]
use core::arch::x86::*;
#[cfg(target_arch = "x86_64")]
use core::arch::x86_64::*;
use half::f16;
pub struct CurrentCpu {}
const STEP: usize = 32;
const EPR: usize = 8;
const ARR: usize = STEP / EPR;
impl Cpu<ARR> for CurrentCpu {
type Unit = __m256;
type... | candle/candle-core/src/cpu/avx.rs/0 | {
"file_path": "candle/candle-core/src/cpu/avx.rs",
"repo_id": "candle",
"token_count": 2094
} | 19 |
//! Types for elements that can be stored and manipulated using tensors.
#![allow(clippy::redundant_closure_call)]
use crate::backend::BackendStorage;
use crate::{CpuStorage, CpuStorageRef, Error, Result};
/// The different types of elements allowed in tensors.
#[derive(Debug, Copy, Clone, PartialEq, Eq, Hash)]
pub en... | candle/candle-core/src/dtype.rs/0 | {
"file_path": "candle/candle-core/src/dtype.rs",
"repo_id": "candle",
"token_count": 3099
} | 20 |
#![allow(unused)]
use super::GgmlDType;
use crate::{Error, MetalDevice, MetalStorage, Result};
pub struct QMetalStorage {
dtype: GgmlDType,
device: MetalDevice,
}
impl QMetalStorage {
pub fn zeros(_: &MetalDevice, _: usize, _: GgmlDType) -> Result<Self> {
Err(Error::NotCompiledWithMetalSupport)
... | candle/candle-core/src/quantized/dummy_metal.rs/0 | {
"file_path": "candle/candle-core/src/quantized/dummy_metal.rs",
"repo_id": "candle",
"token_count": 522
} | 21 |
//! Tensors are N-dimensional matrixes of elements using a single data type.
#![allow(clippy::redundant_closure_call)]
use crate::backend::{BackendDevice, BackendStorage};
use crate::op::{BackpropOp, BinaryOp, CmpOp, Op, ReduceOp, UnaryOp};
use crate::scalar::TensorOrScalar;
use crate::shape::{Dim, Dims};
use crate::{b... | candle/candle-core/src/tensor.rs/0 | {
"file_path": "candle/candle-core/src/tensor.rs",
"repo_id": "candle",
"token_count": 48959
} | 22 |
/// Regression test for pth files not loading on Windows.
#[test]
fn test_pth() {
let tensors = candle_core::pickle::PthTensors::new("tests/test.pt", None).unwrap();
tensors.get("test").unwrap().unwrap();
}
#[test]
fn test_pth_with_key() {
let tensors =
candle_core::pickle::PthTensors::new("tests/t... | candle/candle-core/tests/pth_tests.rs/0 | {
"file_path": "candle/candle-core/tests/pth_tests.rs",
"repo_id": "candle",
"token_count": 440
} | 23 |
//! The MNIST hand-written digit dataset.
//!
//! The files can be obtained from the following link:
//! <http://yann.lecun.com/exdb/mnist/>
use candle::{DType, Device, Error, Result, Tensor};
use hf_hub::{api::sync::Api, Repo, RepoType};
use parquet::file::reader::{FileReader, SerializedFileReader};
use std::fs::File;... | candle/candle-datasets/src/vision/mnist.rs/0 | {
"file_path": "candle/candle-datasets/src/vision/mnist.rs",
"repo_id": "candle",
"token_count": 2133
} | 24 |
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
use candle::{DType, Device, Tensor};
use candle_nn as nn;
use candle_transformers::models::chinese_clip::{ChineseClipConfig, ChineseClipModel};
use clap::Parser;
use tokenizers::Tokenizer;
#[derive(Parser)... | candle/candle-examples/examples/chinese_clip/main.rs/0 | {
"file_path": "candle/candle-examples/examples/chinese_clip/main.rs",
"repo_id": "candle",
"token_count": 3194
} | 25 |
# DeepSeek V2
DeepSeek V2 an MoE model featuring MLA (Multi-Latent Attention). There is a lite (16B) and a full (236B) model.
- Context length of **32k tokens** (Lite model), **128k tokens** (full model)
- 64 routed experts (Lite model), 160 routed experts (full model)
## Running the example
```bash
$ cargo run --e... | candle/candle-examples/examples/deepseekv2/README.md/0 | {
"file_path": "candle/candle-examples/examples/deepseekv2/README.md",
"repo_id": "candle",
"token_count": 316
} | 26 |
# candle-granite LLMs from IBM Research
[Granite](https://www.ibm.com/granite) is a family of Large Language Models built for business, to help drive trust and scalability in AI-driven applications.
## Running the example
```bash
$ cargo run --example granite --features metal -r -- --model-type "granite7b-instruct" ... | candle/candle-examples/examples/granite/README.md/0 | {
"file_path": "candle/candle-examples/examples/granite/README.md",
"repo_id": "candle",
"token_count": 371
} | 27 |
pub enum SeparatorStyle {
Two,
Mpt,
}
pub struct Conversation {
pub system: String,
pub roles: Vec<String>,
pub messages: Vec<(String, Option<String>)>,
pub offset: i32,
pub sep_style: SeparatorStyle,
pub sep: String,
pub sep2: Option<String>,
pub version: String,
}
impl Convers... | candle/candle-examples/examples/llava/conversation.rs/0 | {
"file_path": "candle/candle-examples/examples/llava/conversation.rs",
"repo_id": "candle",
"token_count": 1910
} | 28 |
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
use anyhow::Result;
use candle::{DType, IndexOp, Tensor};
use candle_nn::VarBuilder;
use candle_transformers::models::mimi::{Config, Model};
use clap::{Parser, ValueEnum};
use hf_hub::api::sync::Api;
mod a... | candle/candle-examples/examples/mimi/main.rs/0 | {
"file_path": "candle/candle-examples/examples/mimi/main.rs",
"repo_id": "candle",
"token_count": 3353
} | 29 |
#![allow(dead_code)]
// https://huggingface.co/facebook/musicgen-small/tree/main
// https://github.com/huggingface/transformers/blob/cd4584e3c809bb9e1392ccd3fe38b40daba5519a/src/transformers/models/musicgen/modeling_musicgen.py
// TODO: Add an offline mode.
// TODO: Add a KV cache.
#[cfg(feature = "mkl")]
extern crate... | candle/candle-examples/examples/musicgen/main.rs/0 | {
"file_path": "candle/candle-examples/examples/musicgen/main.rs",
"repo_id": "candle",
"token_count": 1151
} | 30 |
# pixtral
Pixtral-12B is a 12B text+vision model.
[Blog Post](https://mistral.ai/news/pixtral-12b/) -
[HF Model Card](https://huggingface.co/mistralai/Pixtral-12B-2409) -
[HF Community Model Card](https://huggingface.co/mistral-community/pixtral-12b).
```bash
cargo run --profile=release-with-debug --features cuda --... | candle/candle-examples/examples/pixtral/README.md/0 | {
"file_path": "candle/candle-examples/examples/pixtral/README.md",
"repo_id": "candle",
"token_count": 338
} | 31 |
use std::collections::VecDeque;
use candle::{DType, Device, Error, Module, Result, Tensor, Var};
use candle_nn::{
func, linear, sequential::seq, Activation, AdamW, Optimizer, ParamsAdamW, Sequential,
VarBuilder, VarMap,
};
use rand::{distributions::Uniform, thread_rng, Rng};
use super::gym_env::GymEnv;
pub s... | candle/candle-examples/examples/reinforcement-learning/ddpg.rs/0 | {
"file_path": "candle/candle-examples/examples/reinforcement-learning/ddpg.rs",
"repo_id": "candle",
"token_count": 8541
} | 32 |
[
{
"index": 1,
"color": "#787878",
"label": "wall"
},
{
"index": 2,
"color": "#B47878",
"label": "building;edifice"
},
{
"index": 3,
"color": "#06E6E6",
"label": "sky"
},
{
"index": 4,
"color": "#503232",
"label": "floor;flooring"
},
{
"index": 5,
... | candle/candle-examples/examples/segformer/assets/labels.json/0 | {
"file_path": "candle/candle-examples/examples/segformer/assets/labels.json",
"repo_id": "candle",
"token_count": 6397
} | 33 |
mod clip;
mod sampling;
mod vae;
use candle::{DType, IndexOp, Tensor};
use candle_transformers::models::mmdit::model::{Config as MMDiTConfig, MMDiT};
use crate::clip::StableDiffusion3TripleClipWithTokenizer;
use crate::vae::{build_sd3_vae_autoencoder, sd3_vae_vb_rename};
use anyhow::{Ok, Result};
use clap::Parser;
... | candle/candle-examples/examples/stable-diffusion-3/main.rs/0 | {
"file_path": "candle/candle-examples/examples/stable-diffusion-3/main.rs",
"repo_id": "candle",
"token_count": 4715
} | 34 |
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
use anyhow::Error as E;
use clap::{Parser, ValueEnum};
use candle::{DType, Tensor};
use candle_examples::token_output_stream::TokenOutputStream;
use candle_nn::VarBuilder;
use candle_transformers::models::... | candle/candle-examples/examples/trocr/main.rs/0 | {
"file_path": "candle/candle-examples/examples/trocr/main.rs",
"repo_id": "candle",
"token_count": 2167
} | 35 |
#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": 1818
} | 36 |
use anyhow::Result;
use candle::{DType, Device, IndexOp, Tensor, D};
fn to_vec3_round(t: Tensor, digits: i32) -> Result<Vec<Vec<Vec<f32>>>> {
let b = 10f32.powi(digits);
let t = t.to_vec3::<f32>()?;
let t = t
.iter()
.map(|t| {
t.iter()
.map(|t| t.iter().map(|t| ... | candle/candle-flash-attn/tests/flash_attn_tests.rs/0 | {
"file_path": "candle/candle-flash-attn/tests/flash_attn_tests.rs",
"repo_id": "candle",
"token_count": 3779
} | 37 |
// Adapted from https://github.com/ggerganov/llama.cpp/blob/master/ggml-cuda/argsort.cu
#define SORT_ORDER_ASC 1
#define SORT_ORDER_DESC 0
#include "cuda_utils.cuh"
#include<stdint.h>
template<typename T>
static inline __device__ void ggml_cuda_swap(T & a, T & b) {
T tmp = a;
a = b;
b = tmp;
}
template<in... | candle/candle-kernels/src/sort.cu/0 | {
"file_path": "candle/candle-kernels/src/sort.cu",
"repo_id": "candle",
"token_count": 1469
} | 38 |
// Imported from https://github.com/ggerganov/llama.cpp/blob/master/ggml-metal.metal
#include <metal_stdlib>
using namespace metal;
#define MAX(x, y) ((x) > (y) ? (x) : (y))
#define MIN(x, y) ((x) < (y) ? (x) : (y))
#define SWAP(x, y) { auto tmp = (x); (x) = (y); (y) = tmp; }
#define QK4_0 32
#define QR4_0 2
typedef... | candle/candle-metal-kernels/src/quantized.metal/0 | {
"file_path": "candle/candle-metal-kernels/src/quantized.metal",
"repo_id": "candle",
"token_count": 97299
} | 39 |
# candle-nn
| candle/candle-nn/README.md/0 | {
"file_path": "candle/candle-nn/README.md",
"repo_id": "candle",
"token_count": 5
} | 40 |
//! Cache Implementations
//!
use candle::{Device, Result, Tensor};
#[derive(Debug, Clone)]
pub struct Cache {
// all_data is an option on a Tensor, this makes it possible to only create the actual tensor
// on the first call where the batch size is easily known.
// Also this makes it safe to clone a KvCac... | candle/candle-nn/src/kv_cache.rs/0 | {
"file_path": "candle/candle-nn/src/kv_cache.rs",
"repo_id": "candle",
"token_count": 5654
} | 41 |
#[cfg(feature = "mkl")]
extern crate intel_mkl_src;
#[cfg(feature = "accelerate")]
extern crate accelerate_src;
use candle::test_utils::to_vec0_round;
use candle::{Device, Result, Tensor};
/* Equivalent python code:
import torch
import torch.nn.functional as F
input = torch.tensor([
[ 1.1050, 0.3013, -1.5394, -... | candle/candle-nn/tests/loss.rs/0 | {
"file_path": "candle/candle-nn/tests/loss.rs",
"repo_id": "candle",
"token_count": 1344
} | 42 |
from .module import Module
from typing import Optional, Tuple, Any
from candle import Tensor
import candle
class Embedding(Module):
"""A simple lookup table that stores embeddings of a fixed dictionary and size.
This module is often used to store word embeddings and retrieve them using indices.
The input... | candle/candle-pyo3/py_src/candle/nn/sparse.py/0 | {
"file_path": "candle/candle-pyo3/py_src/candle/nn/sparse.py",
"repo_id": "candle",
"token_count": 590
} | 43 |
//! Implementation of BLIP text encoder/decoder.
//!
//! - 📝 [Paper](https://arxiv.org/abs/2201.12086). BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation"
//!
//! - ⚡ [Interactive Wasm Example](https://huggingface.co/spaces/radames/Candle-BLIP-Image-Captioning)
//... | candle/candle-transformers/src/models/blip_text.rs/0 | {
"file_path": "candle/candle-transformers/src/models/blip_text.rs",
"repo_id": "candle",
"token_count": 7345
} | 44 |
//! Implementation of the DINOv2 models from Meta Research.
//!
//! This module implements the DINOv2 vision transformer model from Meta AI Research.
//! DINOv2 is a self-supervised learning model that can learn visual features
//! without using any labeled data. See: ["DINOv2: Learning Robust Visual Features without S... | candle/candle-transformers/src/models/dinov2.rs/0 | {
"file_path": "candle/candle-transformers/src/models/dinov2.rs",
"repo_id": "candle",
"token_count": 6312
} | 45 |
//! mimi model
//!
//! [Mimi](https://huggingface.co/kyutai/mimi) is a state of the art audio
//! compression model using an encoder/decoder architecture with residual vector
//! quantization. The candle implementation supports streaming meaning that it's
//! possible to encode or decode a stream of audio tokens on the... | candle/candle-transformers/src/models/mimi/mod.rs/0 | {
"file_path": "candle/candle-transformers/src/models/mimi/mod.rs",
"repo_id": "candle",
"token_count": 480
} | 46 |
//! ModernBERT
//!
//! ModernBERT is a modernized bidirectional encoder-only Transformer model.
//! - [Arxiv](https://arxiv.org/abs/2412.13663) "Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference"
//! - Upstream [Github repo](https://git... | candle/candle-transformers/src/models/modernbert.rs/0 | {
"file_path": "candle/candle-transformers/src/models/modernbert.rs",
"repo_id": "candle",
"token_count": 6231
} | 47 |
use candle::{DType, Device, Module, Result, Tensor, D};
use candle_nn::{linear_b, rms_norm, Linear, RmsNorm, VarBuilder};
fn default_act() -> candle_nn::Activation {
candle_nn::Activation::Silu
}
fn default_hidden_size() -> usize {
1024
}
fn default_intermediate_size() -> usize {
4096
}
fn default_num_c... | candle/candle-transformers/src/models/pixtral/vision_model.rs/0 | {
"file_path": "candle/candle-transformers/src/models/pixtral/vision_model.rs",
"repo_id": "candle",
"token_count": 5788
} | 48 |
//! Module for quantized StableLM implementation.
//!
//! StableLM is a series of open-source large language models
//! optimized for performance and stability. This implementation
//! provides quantization support for efficient model deployment.
//!
//! Key characteristics:
//! - RMSNorm for layer normalization
//! - ... | candle/candle-transformers/src/models/quantized_stable_lm.rs/0 | {
"file_path": "candle/candle-transformers/src/models/quantized_stable_lm.rs",
"repo_id": "candle",
"token_count": 5352
} | 49 |
use candle::{Result, Tensor};
use candle_nn::{layer_norm, LayerNorm, Linear, Module, VarBuilder};
#[derive(Debug)]
struct Attention {
q_proj: Linear,
k_proj: Linear,
v_proj: Linear,
out_proj: Linear,
num_heads: usize,
}
impl Attention {
fn new(
embedding_dim: usize,
num_heads: ... | candle/candle-transformers/src/models/segment_anything/transformer.rs/0 | {
"file_path": "candle/candle-transformers/src/models/segment_anything/transformer.rs",
"repo_id": "candle",
"token_count": 3597
} | 50 |
//! StableLM model implementation.
//!
//! StableLM is a family of language models trained by Stability AI.
//! This implementation supports the StableLM architecture.
//!
//! Key characteristics:
//! - Grouped query attention (GQA)
//! - Layer normalization
//! - Rotary positional embeddings (RoPE)
//! - Support for d... | candle/candle-transformers/src/models/stable_lm.rs/0 | {
"file_path": "candle/candle-transformers/src/models/stable_lm.rs",
"repo_id": "candle",
"token_count": 7688
} | 51 |
//! Würstchen Efficient Diffusion Model
//!
//! Würstchen is an efficient diffusion model architecture for generating images using
//! a two-stage approach with a small decoder and prior network.
//!
//! - 💻 [GH Link](https://github.com/dome272/Wuerstchen)
//! - 🤗 [HF Link](https://github.com/huggingface/diffusers/bl... | candle/candle-transformers/src/models/wuerstchen/mod.rs/0 | {
"file_path": "candle/candle-transformers/src/models/wuerstchen/mod.rs",
"repo_id": "candle",
"token_count": 302
} | 52 |
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8" />
<title>Welcome to Candle!</title>
<link data-trunk rel="copy-file" href="tokenizer.json" />
<link data-trunk rel="copy-file" href="model.bin" />
<link data-trunk rel="rust" href="Cargo.toml" data-bin="app" data-type="main" />
<l... | candle/candle-wasm-examples/llama2-c/index.html/0 | {
"file_path": "candle/candle-wasm-examples/llama2-c/index.html",
"repo_id": "candle",
"token_count": 315
} | 53 |
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