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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/bark/test_processor_bark.py/0
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355
# coding=utf-8 # Copyright 2023 The Intel Labs Team Authors, The Microsoft Research Team Authors and HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License a...
transformers/tests/models/bridgetower/test_modeling_bridgetower.py/0
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356
# coding=utf-8 # Copyright 2023 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/clvp/test_modeling_clvp.py/0
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357
# 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/convnext/test_modeling_convnext.py/0
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""" Testing suite for the Tensorflow CvT model. """ from __future__ import annotations import inspect import unittest from math import floor import numpy as np from transformers import CvtConfig from transformers.testing_utils import require_tf, require_vision, slow from transformers.utils import cached_property, ...
transformers/tests/models/cvt/test_modeling_tf_cvt.py/0
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359
# 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/dinat/test_modeling_dinat.py/0
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# coding=utf-8 # Copyright 2020 Huggingface # # 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 ...
transformers/tests/models/dpr/test_modeling_tf_dpr.py/0
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361
import unittest import numpy as np from transformers import ElectraConfig, is_flax_available from transformers.testing_utils import require_flax, slow from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask if is_flax_available(): from transformers.models.electra.modeli...
transformers/tests/models/electra/test_modeling_flax_electra.py/0
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362
# 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/esm/test_modeling_esm.py/0
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363
# 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/gpt_neo/test_modeling_gpt_neo.py/0
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364
# 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/graphormer/test_modeling_graphormer.py/0
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365
# coding=utf-8 # Copyright 2021 HuggingFace Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or ag...
transformers/tests/models/imagegpt/test_image_processing_imagegpt.py/0
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366
# coding=utf-8 # Copyright 2018 The Microsoft Research Asia LayoutLM Team Authors, The Hugging Face 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/license...
transformers/tests/models/layoutlm/test_tokenization_layoutlm.py/0
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367
# coding=utf-8 # Copyright 2020 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless requir...
transformers/tests/models/longformer/test_modeling_tf_longformer.py/0
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368
# 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/marian/test_modeling_flax_marian.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_tokenization_mgp_str.py/0
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370
# Copyright 2022 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
transformers/tests/models/opt/test_modeling_flax_opt.py/0
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371
# coding=utf-8 # Copyright 2023 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/pix2struct/test_modeling_pix2struct.py/0
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372
# coding=utf-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 requir...
transformers/tests/models/roformer/test_tokenization_roformer.py/0
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373
# 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/segformer/test_modeling_segformer.py/0
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374
# 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/speech_to_text/test_modeling_tf_speech_to_text.py/0
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375
# 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/tvlt/test_feature_extraction_tvlt.py/0
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376
# coding=utf-8 # Copyright 2021 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/vision_text_dual_encoder/test_modeling_tf_vision_text_dual_encoder.py/0
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377
# coding=utf-8 # Copyright 2021 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/wav2vec2/test_modeling_wav2vec2.py/0
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378
# coding=utf-8 # Copyright 2022 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/whisper/test_modeling_flax_whisper.py/0
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379
# 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_translation.py/0
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380
# 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
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381
# 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
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382
# 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/test_processing_common.py/0
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383
# coding=utf-8 # Copyright 2023 HuggingFace Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or ag...
transformers/tests/tools/test_text_question_answering.py/0
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384
# Copyright 2022 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
transformers/tests/utils/test_add_new_model_like.py/0
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385
# 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/utils/test_modeling_tf_core.py/0
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386
# coding=utf-8 # Copyright 2020 The HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable...
transformers/utils/check_repo.py/0
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387
# 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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388
from transformers import BertTokenizerFast from .custom_tokenization import CustomTokenizer class CustomTokenizerFast(BertTokenizerFast): slow_tokenizer_class = CustomTokenizer pass
transformers/utils/test_module/custom_tokenization_fast.py/0
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389
export WANDB_ENTITY=huggingface export WANDB_PROJECT=trl bash $BENCHMARK_SCRIPT > output.txt # Extract Job IDs into an array job_ids=($(grep "Job ID:" output.txt | awk '{print $3}')) # Extract WANDB_TAGS into an array WANDB_TAGS=($(grep "WANDB_TAGS:" output.txt | awk '{print $2}')) WANDB_TAGS=($(echo $WANDB_TAGS | tr...
trl/benchmark/benchmark_and_report.sh/0
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390
- sections: - local: index title: TRL - local: quickstart title: Quickstart - local: installation title: Installation - local: how_to_train title: PPO Training FAQ - local: use_model title: Use Trained Models - local: customization title: Customize the Training - local: logging ...
trl/docs/source/_toctree.yml/0
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391
# PPO Trainer TRL supports the [PPO](https://arxiv.org/abs/1707.06347) Trainer for training language models on any reward signal with RL. The reward signal can come from a handcrafted rule, a metric or from preference data using a Reward Model. For a full example have a look at [`examples/notebooks/gpt2-sentiment.ipyn...
trl/docs/source/ppo_trainer.mdx/0
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392
# 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...
trl/examples/research_projects/tools/triviaqa.py/0
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393
""" trl is an open library for RL with transformer models. Note: VERSION needs to be formatted following the MAJOR.MINOR.PATCH convention (we need to follow this convention to be able to retrieve versioned scripts) Simple check list for release from AllenNLP repo: https://github.com/allenai/allennlp/blob/maste...
trl/setup.py/0
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394
# Copyright 2023 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
trl/tests/test_no_peft.py/0
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395
# 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...
trl/trl/models/modeling_base.py/0
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396
# 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...
trl/trl/trainer/utils.py/0
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397
# Big model inference benchmarks Running inference with Accelerate on big models. ## Setup These benchmarks use the `transformers` library: ```bash pip install transformers ``` To reproduce or test a new setup, run ```py python inference_acc.py model_name ``` This script supports `gpt-j-6b`, `gpt-neox`, `opt` (3...
accelerate/benchmarks/README.md/0
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0
<!--Copyright 2022 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
accelerate/docs/source/concept_guides/gradient_synchronization.md/0
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1
<!--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/megatron_lm.md/0
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2
#!/bin/bash #SBATCH --job-name=multigpu #SBATCH -D . #SBATCH --output=O-%x.%j #SBATCH --error=E-%x.%j #SBATCH --nodes=1 #SBATCH --ntasks-per-node=1 # number of MP tasks #SBATCH --gres=gpu:4 # number of GPUs per node #SBATCH --cpus-per-task=160 # number of cores per tasks #SBATCH --time=0...
accelerate/examples/slurm/submit_multigpu.sh/0
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3
# 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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4
# 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/dataclasses.py/0
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5
# 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/transformer_engine.py/0
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6
# Copyright 2022 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
accelerate/tests/test_examples.py/0
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7
# Copyright 2022 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
accelerate/tests/test_state_checkpointing.py/0
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8
# Copyright 2023 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
alignment-handbook/setup.py/0
{ "file_path": "alignment-handbook/setup.py", "repo_id": "alignment-handbook", "token_count": 1995 }
9
{ "[python]": { "editor.defaultFormatter": "ms-python.black-formatter" }, "python.formatting.provider": "none", "python.testing.pytestArgs": [ "candle-pyo3" ], "python.testing.unittestEnabled": false, "python.testing.pytestEnabled": true }
candle/.vscode/settings.json/0
{ "file_path": "candle/.vscode/settings.json", "repo_id": "candle", "token_count": 123 }
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# Creating a WASM app
candle/candle-book/src/apps/wasm.md/0
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# Fine-tuning
candle/candle-book/src/training/finetuning.md/0
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#[cfg(feature = "mkl")] extern crate intel_mkl_src; #[cfg(feature = "accelerate")] extern crate accelerate_src; use std::str::FromStr; use anyhow::Result; use candle_core::{Device, Tensor}; fn cos_sin(n: usize, device: &Device) -> Result<Tensor> { let thetas: Vec<_> = (0..n).map(|i| (i as f32 / n as f32)).colle...
candle/candle-core/examples/cuda_sum_benchmark.rs/0
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use crate::backend::BackendDevice; use crate::cpu_backend::CpuDevice; use crate::{CpuStorage, DType, Result, Shape, Storage, WithDType}; /// A `DeviceLocation` represents a physical device whereas multiple `Device` /// can live on the same location (typically for cuda devices). #[derive(Debug, Copy, Clone, PartialEq, ...
candle/candle-core/src/device.rs/0
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//! Support for the GGUF file format. //! //! Spec: https://github.com/philpax/ggml/blob/gguf-spec/docs/gguf.md use super::{GgmlDType, QTensor}; use crate::{Device, Result}; use byteorder::{LittleEndian, ReadBytesExt, WriteBytesExt}; use std::collections::HashMap; pub const DEFAULT_ALIGNMENT: u64 = 32; #[derive(Debu...
candle/candle-core/src/quantized/gguf_file.rs/0
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use anyhow::Result; use candle_core::{test_device, test_utils, Device, IndexOp, Tensor}; /* This test is based on the following script. import torch torch.manual_seed(4242) t = torch.randn((1, 4, 5)) w = torch.randn((2, 4, 3)) print(t.flatten()) print(w.flatten()) res = torch.nn.functional.conv1d(t, w) print(res.flat...
candle/candle-core/tests/conv_tests.rs/0
{ "file_path": "candle/candle-core/tests/conv_tests.rs", "repo_id": "candle", "token_count": 14583 }
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use hf_hub::{ api::sync::{Api, ApiRepo}, Repo, RepoType, }; use parquet::file::reader::SerializedFileReader; use std::fs::File; #[derive(thiserror::Error, Debug)] pub enum Error { #[error("ApiError : {0}")] ApiError(#[from] hf_hub::api::sync::ApiError), #[error("IoError : {0}")] IoError(#[from...
candle/candle-datasets/src/hub.rs/0
{ "file_path": "candle/candle-datasets/src/hub.rs", "repo_id": "candle", "token_count": 900 }
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use crate::model::{Cache, Config, Llama}; use candle::{DType, Device, Result}; use candle_datasets::nlp::tinystories::{Dataset, DatasetRandomIter}; use candle_nn::Optimizer; fn valid_loss( dataset: &Dataset, model: &Llama, args: &crate::TrainingCmd, device: &Device, ) -> Result<f64> { let iter = Da...
candle/candle-examples/examples/llama2-c/training.rs/0
{ "file_path": "candle/candle-examples/examples/llama2-c/training.rs", "repo_id": "candle", "token_count": 1126 }
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use crate::nn::conv1d_weight_norm; use candle::{DType, IndexOp, Module, Result, Tensor}; use candle_nn::{conv1d, Conv1d, Conv1dConfig, VarBuilder}; // Encodec Model // https://github.com/huggingface/transformers/blob/main/src/transformers/models/encodec/modeling_encodec.py #[derive(Debug, Clone, PartialEq)] enum Norm...
candle/candle-examples/examples/musicgen/encodec_model.rs/0
{ "file_path": "candle/candle-examples/examples/musicgen/encodec_model.rs", "repo_id": "candle", "token_count": 9178 }
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use std::collections::VecDeque; use std::fmt::Display; 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::...
candle/candle-examples/examples/reinforcement-learning/ddpg.rs/0
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//! SAM: Segment Anything Model //! https://github.com/facebookresearch/segment-anything #[cfg(feature = "mkl")] extern crate intel_mkl_src; #[cfg(feature = "accelerate")] extern crate accelerate_src; use candle::DType; use candle_nn::VarBuilder; use candle_transformers::models::segment_anything::sam; use clap::Pars...
candle/candle-examples/examples/segment-anything/main.rs/0
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# candle-whisper: speech recognition An implementation of [OpenAI Whisper](https://github.com/openai/whisper) using candle. Whisper is a general purpose speech recognition model, it can be used to convert audio files (in the `.wav` format) to text. Supported features include language detection as well as multilingual ...
candle/candle-examples/examples/whisper/README.md/0
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/****************************************************************************** * Copyright (c) 2023, Tri Dao. ******************************************************************************/ #pragma once #include <cute/algorithm/copy.hpp> #include <cutlass/cutlass.h> #include <cutlass/array.h> #include <cutlass/nu...
candle/candle-flash-attn/kernels/flash_fwd_kernel.h/0
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#include "cuda_utils.cuh" #define BINARY_OP_OUT(TYPENAME, OUT_TYPENAME, FN_NAME, FUNC) \ extern "C" __global__ void FN_NAME( \ const size_t numel, \ const size_t num_dims, \ const size_t *dims_and_strides, \ const TYPENAME *lhs, \ const TYPENAME *rhs, \ OUT_TYPENAME *out \ ) { \ const size_...
candle/candle-kernels/src/binary_op_macros.cuh/0
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template <typename T> METAL_FUNC void im2col( constant size_t &dst_numel, constant size_t &h_out, constant size_t &w_out, constant size_t &h_k, constant size_t &w_k, constant size_t &stride, constant size_t &padding, constant size_t &dilation, constant size_t *src_dims, constant ...
candle/candle-metal-kernels/src/conv.metal/0
{ "file_path": "candle/candle-metal-kernels/src/conv.metal", "repo_id": "candle", "token_count": 3054 }
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#[cfg(feature = "mkl")] extern crate intel_mkl_src; #[cfg(feature = "accelerate")] extern crate accelerate_src; use candle::{DType, Device, Result, Tensor}; use candle_nn::{linear, AdamW, Linear, Module, Optimizer, ParamsAdamW, VarBuilder, VarMap}; fn gen_data() -> Result<(Tensor, Tensor)> { // Generate some sam...
candle/candle-nn/examples/basic_optimizer.rs/0
{ "file_path": "candle/candle-nn/examples/basic_optimizer.rs", "repo_id": "candle", "token_count": 595 }
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//! Recurrent Neural Networks use candle::{DType, Device, IndexOp, Result, Tensor}; /// Trait for Recurrent Neural Networks. #[allow(clippy::upper_case_acronyms)] pub trait RNN { type State: Clone; /// A zero state from which the recurrent network is usually initialized. fn zero_state(&self, batch_dim: us...
candle/candle-nn/src/rnn.rs/0
{ "file_path": "candle/candle-nn/src/rnn.rs", "repo_id": "candle", "token_count": 4874 }
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use candle::Result; use prost::Message; pub mod onnx { include!(concat!(env!("OUT_DIR"), "/onnx.rs")); } pub mod eval; pub use eval::{dtype, simple_eval}; pub fn read_file<P: AsRef<std::path::Path>>(p: P) -> Result<onnx::ModelProto> { let buf = std::fs::read(p)?; onnx::ModelProto::decode(buf.as_slice())....
candle/candle-onnx/src/lib.rs/0
{ "file_path": "candle/candle-onnx/src/lib.rs", "repo_id": "candle", "token_count": 154 }
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from .module import Module from .container import Sequential, ModuleList, ModuleDict from .sparse import Embedding from .normalization import LayerNorm from .linear import Linear
candle/candle-pyo3/py_src/candle/nn/__init__.py/0
{ "file_path": "candle/candle-pyo3/py_src/candle/nn/__init__.py", "repo_id": "candle", "token_count": 43 }
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use ::candle::Tensor; use pyo3::prelude::*; #[derive(Clone, Debug)] /// Represents an absolute shape e.g. (1, 2, 3) pub struct PyShape(Vec<usize>); impl<'source> pyo3::FromPyObject<'source> for PyShape { fn extract(ob: &'source PyAny) -> PyResult<Self> { if ob.is_none() { return Err(PyErr::new...
candle/candle-pyo3/src/shape.rs/0
{ "file_path": "candle/candle-pyo3/src/shape.rs", "repo_id": "candle", "token_count": 1646 }
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use super::with_tracing::{layer_norm, linear, LayerNorm, Linear}; use candle::{DType, Device, Result, Tensor}; use candle_nn::{embedding, Embedding, Module, VarBuilder}; use serde::Deserialize; pub const DTYPE: DType = DType::F32; #[derive(Debug, Clone, Copy, PartialEq, Eq, Deserialize)] #[serde(rename_all = "lowerca...
candle/candle-transformers/src/models/bert.rs/0
{ "file_path": "candle/candle-transformers/src/models/bert.rs", "repo_id": "candle", "token_count": 7941 }
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use crate::models::with_tracing::{linear_no_bias, Linear}; /// Mixtral Model /// https://github.com/huggingface/transformers/blob/main/src/transformers/models/mixtral/modeling_mixtral.py /// https://mistral.ai/news/mixtral-of-experts/ use candle::{DType, Device, Module, Result, Tensor, D}; use candle_nn::{Activation, V...
candle/candle-transformers/src/models/mixtral.rs/0
{ "file_path": "candle/candle-transformers/src/models/mixtral.rs", "repo_id": "candle", "token_count": 9339 }
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//! ResNet implementation. //! //! See "Deep Residual Learning for Image Recognition" He et al. 2015 //! <https://arxiv.org/abs/1512.03385> use candle::{Result, D}; use candle_nn::{batch_norm, Conv2d, Func, VarBuilder}; fn conv2d( c_in: usize, c_out: usize, ksize: usize, padding: usize, stride: usi...
candle/candle-transformers/src/models/resnet.rs/0
{ "file_path": "candle/candle-transformers/src/models/resnet.rs", "repo_id": "candle", "token_count": 3959 }
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#![allow(dead_code)] //! # Diffusion pipelines and models //! //! Noise schedulers can be used to set the trade-off between //! inference speed and quality. use candle::{Result, Tensor}; pub trait SchedulerConfig: std::fmt::Debug { fn build(&self, inference_steps: usize) -> Result<Box<dyn Scheduler>>; } /// This ...
candle/candle-transformers/src/models/stable_diffusion/schedulers.rs/0
{ "file_path": "candle/candle-transformers/src/models/stable_diffusion/schedulers.rs", "repo_id": "candle", "token_count": 930 }
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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 }
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//load Candle Bert Module wasm module import init, { Model } from "./build/m.js"; async function fetchArrayBuffer(url) { const cacheName = "bert-candle-cache"; const cache = await caches.open(cacheName); const cachedResponse = await cache.match(url); if (cachedResponse) { const data = await cachedResponse....
candle/candle-wasm-examples/bert/bertWorker.js/0
{ "file_path": "candle/candle-wasm-examples/bert/bertWorker.js", "repo_id": "candle", "token_count": 779 }
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use candle::{DType, Device, Tensor}; use candle_nn::VarBuilder; use candle_transformers::generation::LogitsProcessor; use candle_transformers::models::mixformer::{Config, MixFormerSequentialForCausalLM as MixFormer}; use candle_transformers::models::quantized_mixformer::MixFormerSequentialForCausalLM as QMixFormer; use...
candle/candle-wasm-examples/phi/src/bin/m.rs/0
{ "file_path": "candle/candle-wasm-examples/phi/src/bin/m.rs", "repo_id": "candle", "token_count": 2646 }
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use crate::languages::LANGUAGES; use anyhow::Error as E; use candle::{safetensors::Load, DType, Device, IndexOp, Tensor, D}; use candle_nn::{ops::softmax, VarBuilder}; pub use candle_transformers::models::whisper::{self as m, Config}; use rand::{distributions::Distribution, rngs::StdRng, SeedableRng}; use serde::{Deser...
candle/candle-wasm-examples/whisper/src/worker.rs/0
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[package] name = "candle-wasm-tests" version.workspace = true edition.workspace = true description = "WASM tests for candle" keywords.workspace = true categories.workspace = true [dependencies] candle = { workspace = true } rand = { workspace = true } getrandom = { version = "0.2", features = ["js"] } [dev-dependenci...
candle/candle-wasm-tests/Cargo.toml/0
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import type { BackendModel } from "./server/models"; import type { Message } from "./types/Message"; import { format } from "date-fns"; import type { WebSearch } from "./types/WebSearch"; import { downloadFile } from "./server/files/downloadFile"; import type { Conversation } from "./types/Conversation"; interface bui...
chat-ui/src/lib/buildPrompt.ts/0
{ "file_path": "chat-ui/src/lib/buildPrompt.ts", "repo_id": "chat-ui", "token_count": 1677 }
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<script lang="ts"> import { fade } from "svelte/transition"; import { onDestroy } from "svelte"; import IconChevron from "./icons/IconChevron.svelte"; export let scrollNode: HTMLElement; export { className as class }; let visible = false; let className = ""; let observer: ResizeObserver | null = null; $: if...
chat-ui/src/lib/components/ScrollToBottomBtn.svelte/0
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<script lang="ts"> export let classNames = ""; </script> <svg class={classNames} xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32" > <path d="M28,10V28H10V10H28m0-2H10a2,2...
chat-ui/src/lib/components/icons/IconCopy.svelte/0
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import type { Conversation } from "$lib/types/Conversation"; import type { TextGenerationStreamOutput } from "@huggingface/inference"; import { endpointTgi, endpointTgiParametersSchema } from "./tgi/endpointTgi"; import { z } from "zod"; import endpointAws, { endpointAwsParametersSchema } from "./aws/endpointAws"; impo...
chat-ui/src/lib/server/endpoints/endpoints.ts/0
{ "file_path": "chat-ui/src/lib/server/endpoints/endpoints.ts", "repo_id": "chat-ui", "token_count": 506 }
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import type { YouWebSearch } from "../../types/WebSearch"; import { WebSearchProvider } from "../../types/WebSearch"; import { SERPAPI_KEY, SERPER_API_KEY, SERPSTACK_API_KEY, USE_LOCAL_WEBSEARCH, YDC_API_KEY, } from "$env/static/private"; import { getJson } from "serpapi"; import type { GoogleParameters } from "se...
chat-ui/src/lib/server/websearch/searchWeb.ts/0
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import type { WebSearchSource } from "./WebSearch"; export type FinalAnswer = { type: "finalAnswer"; text: string; }; export type TextStreamUpdate = { type: "stream"; token: string; }; export type AgentUpdate = { type: "agent"; agent: string; content: string; binary?: Blob; }; export type WebSearchUpdate = ...
chat-ui/src/lib/types/MessageUpdate.ts/0
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const file2base64 = (file: File): Promise<string> => { return new Promise<string>((resolve, reject) => { const reader = new FileReader(); reader.readAsDataURL(file); reader.onload = () => { const dataUrl = reader.result as string; const base64 = dataUrl.split(",")[1]; resolve(base64); }; reader.oner...
chat-ui/src/lib/utils/file2base64.ts/0
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<script lang="ts"> import { goto } from "$app/navigation"; import { base } from "$app/paths"; import { PUBLIC_APP_NAME } from "$env/static/public"; import ChatWindow from "$lib/components/chat/ChatWindow.svelte"; import { ERROR_MESSAGES, error } from "$lib/stores/errors"; import { pendingMessage } from "$lib/stor...
chat-ui/src/routes/+page.svelte/0
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import { buildPrompt } from "$lib/buildPrompt"; import { authCondition } from "$lib/server/auth"; import { collections } from "$lib/server/database"; import { models } from "$lib/server/models"; import { error } from "@sveltejs/kit"; import { ObjectId } from "mongodb"; export async function GET({ params, locals }) { ...
chat-ui/src/routes/conversation/[id]/message/[messageId]/prompt/+server.ts/0
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import { collections } from "$lib/server/database"; import { z } from "zod"; import { authCondition } from "$lib/server/auth"; import { DEFAULT_SETTINGS } from "$lib/types/Settings"; export async function POST({ request, locals }) { const body = await request.json(); const { ethicsModalAccepted, ...settings } = z ...
chat-ui/src/routes/settings/+server.ts/0
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{ "$schema": "https://vega.github.io/schema/vega-lite/v4.json", "data": { "values": "<DVC_METRIC_DATA>" }, "title": "<DVC_METRIC_TITLE>", "mark": "rect", "encoding": { "x": { "field": "<DVC_METRIC_X>", "type": "nominal", "sort": "ascending", ...
datasets/.dvc/plots/confusion.json/0
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# Create an audio dataset You can share a dataset with your team or with anyone in the community by creating a dataset repository on the Hugging Face Hub: ```py from datasets import load_dataset dataset = load_dataset("<username>/my_dataset") ``` There are several methods for creating and sharing an audio dataset: ...
datasets/docs/source/audio_dataset.mdx/0
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# Process image data This guide shows specific methods for processing image datasets. Learn how to: - Use [`~Dataset.map`] with image dataset. - Apply data augmentations to a dataset with [`~Dataset.set_transform`]. For a guide on how to process any type of dataset, take a look at the <a class="underline decoration-...
datasets/docs/source/image_process.mdx/0
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# Utilities ## Configure logging 🤗 Datasets strives to be transparent and explicit about how it works, but this can be quite verbose at times. We have included a series of logging methods which allow you to easily adjust the level of verbosity of the entire library. Currently the default verbosity of the library is ...
datasets/docs/source/package_reference/utilities.mdx/0
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stages: benchmark_array_xd: cmd: python ./benchmarks/benchmark_array_xd.py deps: - ./benchmarks/benchmark_array_xd.py metrics: - ./benchmarks/results/benchmark_array_xd.json: cache: false benchmark_indices_mapping: cmd: python ./benchmarks/benchmark_indices_mapping.py deps: ...
datasets/dvc.yaml/0
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# Metric Card for COMET ## Metric description Crosslingual Optimized Metric for Evaluation of Translation (COMET) is an open-source framework used to train Machine Translation metrics that achieve high levels of correlation with different types of human judgments. ## How to use COMET takes 3 lists of strings as inp...
datasets/metrics/comet/README.md/0
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# Copyright 2020 The HuggingFace Datasets Authors. # # 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 ...
datasets/metrics/glue/glue.py/0
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