text stringlengths 7 1.24M | id stringlengths 14 166 | metadata dict | __index_level_0__ int64 0 519 |
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# coding=utf-8
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | transformers/tests/models/hiera/test_modeling_hiera.py/0 | {
"file_path": "transformers/tests/models/hiera/test_modeling_hiera.py",
"repo_id": "transformers",
"token_count": 12031
} | 437 |
# 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 | {
"file_path": "transformers/tests/models/imagegpt/test_image_processing_imagegpt.py",
"repo_id": "transformers",
"token_count": 4831
} | 438 |
# coding=utf-8
# Copyright 2023 Microsoft Research and The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/L... | transformers/tests/models/kosmos2/test_processor_kosmos2.py/0 | {
"file_path": "transformers/tests/models/kosmos2/test_processor_kosmos2.py",
"repo_id": "transformers",
"token_count": 9851
} | 439 |
# coding=utf-8
# Copyright 2022 Google LongT5 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 ... | transformers/tests/models/longt5/test_modeling_longt5.py/0 | {
"file_path": "transformers/tests/models/longt5/test_modeling_longt5.py",
"repo_id": "transformers",
"token_count": 30001
} | 440 |
# 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 | {
"file_path": "transformers/tests/models/marian/test_modeling_flax_marian.py",
"repo_id": "transformers",
"token_count": 8242
} | 441 |
# 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/mobilenet_v2/test_modeling_mobilenet_v2.py/0 | {
"file_path": "transformers/tests/models/mobilenet_v2/test_modeling_mobilenet_v2.py",
"repo_id": "transformers",
"token_count": 5524
} | 442 |
# 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 | {
"file_path": "transformers/tests/models/mt5/test_modeling_flax_mt5.py",
"repo_id": "transformers",
"token_count": 950
} | 443 |
# 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/nllb/test_tokenization_nllb.py/0 | {
"file_path": "transformers/tests/models/nllb/test_tokenization_nllb.py",
"repo_id": "transformers",
"token_count": 9740
} | 444 |
# 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/openai/test_modeling_tf_openai.py/0 | {
"file_path": "transformers/tests/models/openai/test_modeling_tf_openai.py",
"repo_id": "transformers",
"token_count": 5003
} | 445 |
# coding=utf-8
# Copyright 2023 IBM and HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unle... | transformers/tests/models/patchtsmixer/test_modeling_patchtsmixer.py/0 | {
"file_path": "transformers/tests/models/patchtsmixer/test_modeling_patchtsmixer.py",
"repo_id": "transformers",
"token_count": 20492
} | 446 |
# coding=utf-8
# Copyright 2023 Microsoft and the HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.... | transformers/tests/models/phi/test_modeling_phi.py/0 | {
"file_path": "transformers/tests/models/phi/test_modeling_phi.py",
"repo_id": "transformers",
"token_count": 11449
} | 447 |
# 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/pop2piano/test_feature_extraction_pop2piano.py/0 | {
"file_path": "transformers/tests/models/pop2piano/test_feature_extraction_pop2piano.py",
"repo_id": "transformers",
"token_count": 4968
} | 448 |
# 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/qwen2_audio/test_modeling_qwen2_audio.py/0 | {
"file_path": "transformers/tests/models/qwen2_audio/test_modeling_qwen2_audio.py",
"repo_id": "transformers",
"token_count": 7262
} | 449 |
# Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | transformers/tests/models/reformer/test_tokenization_reformer.py/0 | {
"file_path": "transformers/tests/models/reformer/test_tokenization_reformer.py",
"repo_id": "transformers",
"token_count": 6425
} | 450 |
# 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/roberta/test_modeling_tf_roberta.py/0 | {
"file_path": "transformers/tests/models/roberta/test_modeling_tf_roberta.py",
"repo_id": "transformers",
"token_count": 12677
} | 451 |
# 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... | transformers/tests/models/rt_detr/test_modeling_rt_detr.py/0 | {
"file_path": "transformers/tests/models/rt_detr/test_modeling_rt_detr.py",
"repo_id": "transformers",
"token_count": 15214
} | 452 |
# 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 | {
"file_path": "transformers/tests/models/speech_encoder_decoder/test_modeling_speech_encoder_decoder.py",
"repo_id": "transformers",
"token_count": 11053
} | 453 |
# 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_tokenization_squeezebert.py/0 | {
"file_path": "transformers/tests/models/squeezebert/test_tokenization_squeezebert.py",
"repo_id": "transformers",
"token_count": 669
} | 454 |
# 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/swin2sr/test_modeling_swin2sr.py/0 | {
"file_path": "transformers/tests/models/swin2sr/test_modeling_swin2sr.py",
"repo_id": "transformers",
"token_count": 6141
} | 455 |
# 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": 15570
} | 456 |
# 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": 13985
} | 457 |
# 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 | {
"file_path": "transformers/tests/models/x_clip/test_modeling_x_clip.py",
"repo_id": "transformers",
"token_count": 12611
} | 458 |
# 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 | {
"file_path": "transformers/tests/models/xlm_roberta_xl/test_modeling_xlm_roberta_xl.py",
"repo_id": "transformers",
"token_count": 12097
} | 459 |
# 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/optimization/test_optimization.py/0 | {
"file_path": "transformers/tests/optimization/test_optimization.py",
"repo_id": "transformers",
"token_count": 4041
} | 460 |
# 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/pipelines/test_pipelines_mask_generation.py/0 | {
"file_path": "transformers/tests/pipelines/test_pipelines_mask_generation.py",
"repo_id": "transformers",
"token_count": 3341
} | 461 |
# 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_zero_shot_object_detection.py/0 | {
"file_path": "transformers/tests/pipelines/test_pipelines_zero_shot_object_detection.py",
"repo_id": "transformers",
"token_count": 5112
} | 462 |
# coding=utf-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 requir... | transformers/tests/quantization/gptq/test_gptq.py/0 | {
"file_path": "transformers/tests/quantization/gptq/test_gptq.py",
"repo_id": "transformers",
"token_count": 7206
} | 463 |
#!/usr/bin/env python
# coding=utf-8
# Copyright 2021 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | transformers/tests/sagemaker/scripts/pytorch/run_glue_model_parallelism.py/0 | {
"file_path": "transformers/tests/sagemaker/scripts/pytorch/run_glue_model_parallelism.py",
"repo_id": "transformers",
"token_count": 9577
} | 464 |
# 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 | {
"file_path": "transformers/tests/test_processing_common.py",
"repo_id": "transformers",
"token_count": 5765
} | 465 |
# 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_tf.py/0 | {
"file_path": "transformers/tests/utils/test_activations_tf.py",
"repo_id": "transformers",
"token_count": 803
} | 466 |
# 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_hub_utils.py/0 | {
"file_path": "transformers/tests/utils/test_hub_utils.py",
"repo_id": "transformers",
"token_count": 2860
} | 467 |
# 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/add_pipeline_model_mapping_to_test.py/0 | {
"file_path": "transformers/utils/add_pipeline_model_mapping_to_test.py",
"repo_id": "transformers",
"token_count": 5411
} | 468 |
# coding=utf-8
# Copyright 2022 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | transformers/utils/create_dummy_models.py/0 | {
"file_path": "transformers/utils/create_dummy_models.py",
"repo_id": "transformers",
"token_count": 29298
} | 469 |
# 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/utils/notification_service_quantization.py/0 | {
"file_path": "transformers/utils/notification_service_quantization.py",
"repo_id": "transformers",
"token_count": 4809
} | 470 |
import numpy as np
from transformers import Pipeline
def softmax(outputs):
maxes = np.max(outputs, axis=-1, keepdims=True)
shifted_exp = np.exp(outputs - maxes)
return shifted_exp / shifted_exp.sum(axis=-1, keepdims=True)
class PairClassificationPipeline(Pipeline):
def _sanitize_parameters(self, **... | transformers/utils/test_module/custom_pipeline.py/0 | {
"file_path": "transformers/utils/test_module/custom_pipeline.py",
"repo_id": "transformers",
"token_count": 453
} | 471 |
# pip install openrlbenchmark==0.2.1a5
# see https://github.com/openrlbenchmark/openrlbenchmark#get-started for documentation
BASELINE_PR_TAG=v0.4.7-55-g110e672
BASELINE_PR_NAME=PR-662
python -m openrlbenchmark.rlops_multi_metrics \
--filters '?we=huggingface&wpn=trl&xaxis=_step&ceik=trl_ppo_trainer_config.value.r... | trl/benchmark/plot.sh/0 | {
"file_path": "trl/benchmark/plot.sh",
"repo_id": "trl",
"token_count": 1454
} | 472 |
# CPO Trainer
Contrastive Preference Optimization (CPO) as introduced in the paper [Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation](https://huggingface.co/papers/2401.08417) by Haoran Xu, Amr Sharaf, Yunmo Chen, Weiting Tan, Lingfeng Shen, Benjamin Van Durme, Kent... | trl/docs/source/cpo_trainer.mdx/0 | {
"file_path": "trl/docs/source/cpo_trainer.mdx",
"repo_id": "trl",
"token_count": 1761
} | 473 |
# Multi Adapter RL (MARL) - a single base model for everything
Here we present an approach that uses a single base model for the entire PPO algorithm - which includes retrieving the reference logits, computing the active logits and the rewards. This feature is experimental as we did not test the convergence of the app... | trl/docs/source/multi_adapter_rl.mdx/0 | {
"file_path": "trl/docs/source/multi_adapter_rl.mdx",
"repo_id": "trl",
"token_count": 1207
} | 474 |
# RLHF pipeline for the creation of StackLLaMa: a Stack exchange llama-7b model.
There were three main steps to the training process:
1. Supervised fine-tuning of the base llama-7b model to create llama-7b-se:
- `torchrun --nnodes 1 --nproc_per_node 8 examples/research_projects/stack_llama/scripts/supervised_finet... | trl/examples/research_projects/stack_llama/scripts/README.md/0 | {
"file_path": "trl/examples/research_projects/stack_llama/scripts/README.md",
"repo_id": "trl",
"token_count": 696
} | 475 |
"""
Run the BCO training script with the commands below. In general, the optimal configuration for BCO will be similar to that of KTO.
# Full training:
python examples/scripts/bco.py \
--model_name_or_path=nnheui/stablelm-2-1_6b-sft-full \
--per_device_train_batch_size 16 \
--per_device_eval_batch_size 32 ... | trl/examples/scripts/bco.py/0 | {
"file_path": "trl/examples/scripts/bco.py",
"repo_id": "trl",
"token_count": 3288
} | 476 |
# Copyright 2023 metric-space, The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | trl/tests/test_alignprop_trainer.py/0 | {
"file_path": "trl/tests/test_alignprop_trainer.py",
"repo_id": "trl",
"token_count": 1225
} | 477 |
# 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 | {
"file_path": "trl/tests/test_no_peft.py",
"repo_id": "trl",
"token_count": 2576
} | 478 |
# This file is a copy of trl/examples/scripts/sft.py so that we could
# use it together with rich and the TRL CLI in a more customizable manner.
# 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 comp... | trl/trl/commands/cli.py/0 | {
"file_path": "trl/trl/commands/cli.py",
"repo_id": "trl",
"token_count": 929
} | 479 |
import itertools
from contextlib import contextmanager
from dataclasses import dataclass
from typing import TYPE_CHECKING, Literal, Optional, Tuple, Union
from accelerate.utils import is_deepspeed_available
from transformers import PreTrainedModel, PreTrainedTokenizer
from .modeling_value_head import AutoModelForCaus... | trl/trl/models/utils.py/0 | {
"file_path": "trl/trl/models/utils.py",
"repo_id": "trl",
"token_count": 2369
} | 480 |
# Copyright 2024 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | trl/trl/trainer/kto_config.py/0 | {
"file_path": "trl/trl/trainer/kto_config.py",
"repo_id": "trl",
"token_count": 1587
} | 481 |
# 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/trl/trainer/sft_trainer.py/0 | {
"file_path": "trl/trl/trainer/sft_trainer.py",
"repo_id": "trl",
"token_count": 14380
} | 482 |
# 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/benchmarks/fp8/distrib_deepspeed.py/0 | {
"file_path": "accelerate/benchmarks/fp8/distrib_deepspeed.py",
"repo_id": "accelerate",
"token_count": 2963
} | 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/basic_tutorials/overview.md/0 | {
"file_path": "accelerate/docs/source/basic_tutorials/overview.md",
"repo_id": "accelerate",
"token_count": 312
} | 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/checkpoint.md/0 | {
"file_path": "accelerate/docs/source/usage_guides/checkpoint.md",
"repo_id": "accelerate",
"token_count": 1156
} | 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 agreed... | accelerate/docs/source/usage_guides/tracking.md/0 | {
"file_path": "accelerate/docs/source/usage_guides/tracking.md",
"repo_id": "accelerate",
"token_count": 2703
} | 3 |
#!/bin/bash -l
#SBATCH --job-name=multicpu
#SBATCH --nodes=2 # number of Nodes
#SBATCH --ntasks-per-node=1 # number of MP tasks
#SBATCH --exclusive
#SBATCH --output=O-%x.%j
#SBATCH --error=E-%x.%j
######################
### Set enviroment ###
######################
source activateEnv... | accelerate/examples/slurm/submit_multicpu.sh/0 | {
"file_path": "accelerate/examples/slurm/submit_multicpu.sh",
"repo_id": "accelerate",
"token_count": 767
} | 4 |
#!/usr/bin/env python
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unles... | accelerate/src/accelerate/commands/config/update.py/0 | {
"file_path": "accelerate/src/accelerate/commands/config/update.py",
"repo_id": "accelerate",
"token_count": 774
} | 5 |
# 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/src/accelerate/inference.py/0 | {
"file_path": "accelerate/src/accelerate/inference.py",
"repo_id": "accelerate",
"token_count": 2855
} | 6 |
# 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/src/accelerate/test_utils/scripts/external_deps/test_pippy.py/0 | {
"file_path": "accelerate/src/accelerate/test_utils/scripts/external_deps/test_pippy.py",
"repo_id": "accelerate",
"token_count": 1745
} | 7 |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate/src/accelerate/utils/dataclasses.py/0 | {
"file_path": "accelerate/src/accelerate/utils/dataclasses.py",
"repo_id": "accelerate",
"token_count": 42303
} | 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 required by applicabl... | accelerate/src/accelerate/utils/transformer_engine.py/0 | {
"file_path": "accelerate/src/accelerate/utils/transformer_engine.py",
"repo_id": "accelerate",
"token_count": 2373
} | 9 |
compute_environment: LOCAL_MACHINE
deepspeed_config: {}
distributed_type: 'NO'
downcast_bf16: 'no'
fsdp_config: {}
gpu_ids: all
machine_rank: 0
main_process_ip: null
main_process_port: null
main_training_function: main
megatron_lm_config: {}
mixed_precision: 'no'
num_machines: 1
num_processes: 1
rdzv_backend: static
sa... | accelerate/tests/test_configs/latest.yaml/0 | {
"file_path": "accelerate/tests/test_configs/latest.yaml",
"repo_id": "accelerate",
"token_count": 186
} | 10 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | accelerate/tests/test_sagemaker.py/0 | {
"file_path": "accelerate/tests/test_sagemaker.py",
"repo_id": "accelerate",
"token_count": 1007
} | 11 |
# Comparing Preference Alignment Algorithms
This directory contains various comparisons for three algorithms: DPO, IPO, and KTO. Each algorithm has been run in different hyperparameter configurations to study their performance. Two different models and datasets have been used to compare the performance of each algorith... | alignment-handbook/recipes/pref_align_scan/README.md/0 | {
"file_path": "alignment-handbook/recipes/pref_align_scan/README.md",
"repo_id": "alignment-handbook",
"token_count": 691
} | 12 |
# Instructions to Replicate Zephyr 7B Gemma
Similar to how we trained Zephyr 7B Beta in our [technical report](https://huggingface.co/papers/2310.16944), training this model proceeds in two steps:
1. Apply SFT to fine-tune Gemma 7B on the Deita 10k dataset ([link](https://huggingface.co/datasets/HuggingFaceH4/deita-... | alignment-handbook/recipes/zephyr-7b-gemma/README.md/0 | {
"file_path": "alignment-handbook/recipes/zephyr-7b-gemma/README.md",
"repo_id": "alignment-handbook",
"token_count": 505
} | 13 |
# Porting a custom kernel
| candle/candle-book/src/cuda/porting.md/0 | {
"file_path": "candle/candle-book/src/cuda/porting.md",
"repo_id": "candle",
"token_count": 7
} | 14 |
# Simplified
## How its works
This program implements a neural network to predict the winner of the second round of elections based on the results of the first round.
Basic moments:
1. A multilayer perceptron with two hidden layers is used. The first hidden layer has 4 neurons, the second has 2 neurons.
2. The inpu... | candle/candle-book/src/training/simplified.md/0 | {
"file_path": "candle/candle-book/src/training/simplified.md",
"repo_id": "candle",
"token_count": 530
} | 15 |
#[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 | {
"file_path": "candle/candle-core/examples/cuda_sum_benchmark.rs",
"repo_id": "candle",
"token_count": 827
} | 16 |
use crate::backend::BackendDevice;
use crate::{CpuStorage, CpuStorageRef, DType, Layout, Result, Shape};
pub use candle_kernels as kernels;
pub use cudarc;
use cudarc::driver::{CudaFunction, LaunchAsync, LaunchConfig};
use half::{bf16, f16};
use std::sync::{Arc, Mutex};
use super::{CudaError, CudaStorage, CudaStorageS... | candle/candle-core/src/cuda_backend/device.rs/0 | {
"file_path": "candle/candle-core/src/cuda_backend/device.rs",
"repo_id": "candle",
"token_count": 9237
} | 17 |
#![allow(dead_code)]
use libc::{c_char, c_double, c_float, c_int};
mod ffi {
use super::*;
extern "C" {
pub fn vsTanh(n: c_int, a: *const c_float, y: *mut c_float);
pub fn vdTanh(n: c_int, a: *const c_double, y: *mut c_double);
pub fn vsExp(n: c_int, a: *const c_float, y: *mut c_float);... | candle/candle-core/src/mkl.rs/0 | {
"file_path": "candle/candle-core/src/mkl.rs",
"repo_id": "candle",
"token_count": 6463
} | 18 |
use crate::{DType, Device, Error, Result, Tensor, WithDType};
use safetensors::tensor as st;
use safetensors::tensor::SafeTensors;
use std::borrow::Cow;
use std::collections::HashMap;
use std::path::Path;
impl From<DType> for st::Dtype {
fn from(value: DType) -> Self {
match value {
DType::U8 =... | candle/candle-core/src/safetensors.rs/0 | {
"file_path": "candle/candle-core/src/safetensors.rs",
"repo_id": "candle",
"token_count": 8064
} | 19 |
#![allow(clippy::approx_constant)]
use anyhow::{Context, Result};
use candle_core::{test_device, test_utils, Device, Shape, Tensor, Var};
fn simple_grad(device: &Device) -> Result<()> {
let x = Var::new(&[3f32, 1., 4.], device)?;
let x = x.as_tensor();
let y = (((x * x)? + x * 5f64)? + 4f64)?;
let grad... | candle/candle-core/tests/grad_tests.rs/0 | {
"file_path": "candle/candle-core/tests/grad_tests.rs",
"repo_id": "candle",
"token_count": 9105
} | 20 |
# candle-datasets
| candle/candle-datasets/README.md/0 | {
"file_path": "candle/candle-datasets/README.md",
"repo_id": "candle",
"token_count": 7
} | 21 |
# candle-bert
Bert is a general large language model. In this example it can be used for two
different tasks:
- Compute sentence embeddings for a prompt.
- Compute similarities between a set of sentences.
## Sentence embeddings
Bert is used to compute the sentence embeddings for a prompt. The model weights
are down... | candle/candle-examples/examples/bert/README.md/0 | {
"file_path": "candle/candle-examples/examples/bert/README.md",
"repo_id": "candle",
"token_count": 1564
} | 22 |
/*
* Adapted from
* https://github.com/NVIDIA/FasterTransformer/blob/release/v5.3_tag/src/fastertransformer/kernels/reduce_kernel_utils.cuh
* Copyright (c) 2023, The vLLM team.
* Copyright (c) 2020-2023, NVIDIA CORPORATION. All rights reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
... | candle/candle-examples/examples/custom-ops/kernels/reduction_utils.cuh/0 | {
"file_path": "candle/candle-examples/examples/custom-ops/kernels/reduction_utils.cuh",
"repo_id": "candle",
"token_count": 529
} | 23 |
# gte-Qwen1.5-7B-instruct
gte-Qwen1.5-7B-instruct is a variant of the GTE embedding model family.
- [Model card](https://huggingface.co/Alibaba-NLP/gte-Qwen1.5-7B-instruct) on the HuggingFace Hub.
- [Technical report](https://arxiv.org/abs/2308.03281) *Towards General Text Embeddings with Multi-stage Contrastive Lear... | candle/candle-examples/examples/gte-qwen/README.md/0 | {
"file_path": "candle/candle-examples/examples/gte-qwen/README.md",
"repo_id": "candle",
"token_count": 229
} | 24 |
# candle-mamba-minimal: minimal implementation of Mamba
This is based on [mamba-minimal](https://github.com/johnma2006/mamba-minimal).
Compared to the mamba example, this version can handle training but is much
slower.
## Running the example
```bash
$ cargo run --example mamba-minimal --release -- --prompt "Mamba i... | candle/candle-examples/examples/mamba-minimal/README.md/0 | {
"file_path": "candle/candle-examples/examples/mamba-minimal/README.md",
"repo_id": "candle",
"token_count": 206
} | 25 |
#[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, Device, Tensor};
use candle_nn::{ops::softmax, VarBuilder};
use candle_transformers::models::mobileclip;
use tokenizers::Tokenize... | candle/candle-examples/examples/mobileclip/main.rs/0 | {
"file_path": "candle/candle-examples/examples/mobileclip/main.rs",
"repo_id": "candle",
"token_count": 2305
} | 26 |
#[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
} | 27 |
import gymnasium as gym
import numpy as np
from collections import deque
from PIL import Image
from multiprocessing import Process, Pipe
# atari_wrappers.py
class NoopResetEnv(gym.Wrapper):
def __init__(self, env, noop_max=30):
"""Sample initial states by taking random number of no-ops on reset.
No... | candle/candle-examples/examples/reinforcement-learning/atari_wrappers.py/0 | {
"file_path": "candle/candle-examples/examples/reinforcement-learning/atari_wrappers.py",
"repo_id": "candle",
"token_count": 4740
} | 28 |
# candle-segformer
- [HuggingFace Segformer Model Card][segformer]
- [`mit-b0` - An encoder only pretrained model][encoder]
- [`segformer-b0-finetuned-ade-512-512` - A fine tuned model for segmentation][ade512]
## How to run the example
If you want you can use the example images from this [pull request][pr], downloa... | candle/candle-examples/examples/segformer/README.md/0 | {
"file_path": "candle/candle-examples/examples/segformer/README.md",
"repo_id": "candle",
"token_count": 357
} | 29 |
# candle-t5
## Encoder-decoder example:
```bash
$ cargo run --example t5 --release -- --model-id "t5-small" --prompt "translate to German: A beautiful candle." --decode
...
Eine schöne Kerze.
9 tokens generated (2.42 token/s)
```
Variants such as [flan-t5](https://huggingface.co/google/flan-t5-small), [flan-ul2](ht... | candle/candle-examples/examples/t5/README.md/0 | {
"file_path": "candle/candle-examples/examples/t5/README.md",
"repo_id": "candle",
"token_count": 608
} | 30 |
/******************************************************************************
* 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
} | 31 |
use core::ffi::{c_int, c_void};
extern "C" {
pub(crate) fn run_mha(
q_ptr: *const c_void,
k_ptr: *const c_void,
v_ptr: *const c_void,
o_ptr: *const c_void,
softmax_lse_ptr: *const c_void,
alibi_slopes_ptr: *const c_void,
cu_seqlens_q_ptr: *const i32,
... | candle/candle-flash-attn/src/ffi.rs/0 | {
"file_path": "candle/candle-flash-attn/src/ffi.rs",
"repo_id": "candle",
"token_count": 670
} | 32 |
// Kernels adapted from llama.cpp ggml-cuda.cu
// https://github.com/ggerganov/llama.cpp/blob/master/ggml-cuda.cu
#include "cuda_fp16.h"
#include "cuda_bf16.h"
#include<stdint.h>
#define GGML_UNUSED(x) (void)(x)
#define GGML_CUDA_ASSUME(x)
#ifdef GGML_QKK_64
#define QK_K 64
#define K_SCALE_SIZE 4
#else
#define QK_K 2... | candle/candle-kernels/src/quantized.cu/0 | {
"file_path": "candle/candle-kernels/src/quantized.cu",
"repo_id": "candle",
"token_count": 85333
} | 33 |
#include <metal_stdlib>
using namespace metal;
#define MAX(x, y) ((x) > (y) ? (x) : (y))
#define MIN(x, y) ((x) < (y) ? (x) : (y))
METAL_FUNC uint get_strided_index(
uint idx,
constant size_t &num_dims,
constant size_t *dims,
constant size_t *strides
) {
uint strided_i = 0;
for (uint d = 0; d ... | candle/candle-metal-kernels/src/reduce.metal/0 | {
"file_path": "candle/candle-metal-kernels/src/reduce.metal",
"repo_id": "candle",
"token_count": 9140
} | 34 |
#[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
} | 35 |
//! Various optimization algorithms.
use candle::{Result, Tensor, Var};
/// The interface optimizers should implement.
pub trait Optimizer: Sized {
type Config: Sized;
fn new(vars: Vec<Var>, config: Self::Config) -> Result<Self>;
fn step(&mut self, grads: &candle::backprop::GradStore) -> Result<()>;
... | candle/candle-nn/src/optim.rs/0 | {
"file_path": "candle/candle-nn/src/optim.rs",
"repo_id": "candle",
"token_count": 2798
} | 36 |
use std::io::Result;
fn main() -> Result<()> {
prost_build::compile_protos(&["src/onnx.proto3"], &["src/"])?;
Ok(())
}
| candle/candle-onnx/build.rs/0 | {
"file_path": "candle/candle-onnx/build.rs",
"repo_id": "candle",
"token_count": 60
} | 37 |
from dataclasses import dataclass
from typing import Optional
from candle.nn import Module, Embedding, LayerNorm, Linear, ModuleList
from candle import Tensor
import candle
import candle.functional as F
from typing import Tuple, Optional
@dataclass
class Config:
vocab_size: int = 30522
hidden_size: int = 768
... | candle/candle-pyo3/py_src/candle/models/bert.py/0 | {
"file_path": "candle/candle-pyo3/py_src/candle/models/bert.py",
"repo_id": "candle",
"token_count": 3528
} | 38 |
# This example shows how the candle Python api can be used to replicate llama.cpp.
import sys
from typing import Dict, Tuple, Any
import candle
from candle.models.llama import QuantizedLlama
from candle import utils
MAX_SEQ_LEN = 4096
def gguf_rename(tensor_name: str):
if tensor_name == "token_embd.weight":
... | candle/candle-pyo3/quant-llama.py/0 | {
"file_path": "candle/candle-pyo3/quant-llama.py",
"repo_id": "candle",
"token_count": 1318
} | 39 |
# candle-transformers
| candle/candle-transformers/README.md/0 | {
"file_path": "candle/candle-transformers/README.md",
"repo_id": "candle",
"token_count": 6
} | 40 |
/// Adapted from https://github.com/descriptinc/descript-audio-codec
use crate::models::encodec;
use candle::{IndexOp, Result, Tensor, D};
use candle_nn::{Conv1d, Conv1dConfig, ConvTranspose1d, ConvTranspose1dConfig, VarBuilder};
#[derive(serde::Deserialize, Debug, Clone)]
pub struct Config {
pub num_codebooks: us... | candle/candle-transformers/src/models/dac.rs/0 | {
"file_path": "candle/candle-transformers/src/models/dac.rs",
"repo_id": "candle",
"token_count": 5651
} | 41 |
use candle::{Module, Result, Tensor, D};
use candle_nn as nn;
use super::projections::{AttnProjections, Mlp, Qkv, QkvOnlyAttnProjections};
pub struct ModulateIntermediates {
gate_msa: Tensor,
shift_mlp: Tensor,
scale_mlp: Tensor,
gate_mlp: Tensor,
}
pub struct DiTBlock {
norm1: LayerNormNoAffine,... | candle/candle-transformers/src/models/mmdit/blocks.rs/0 | {
"file_path": "candle/candle-transformers/src/models/mmdit/blocks.rs",
"repo_id": "candle",
"token_count": 4866
} | 42 |
use crate::models::with_tracing::{layer_norm, linear, Embedding, LayerNorm, Linear};
/// Phi model.
/// https://huggingface.co/microsoft/phi-2
/// There is an alternative implementation of the phi model in mixformers.rs.
/// This corresponds to the model update made with the following commit:
/// https://huggingface.co... | candle/candle-transformers/src/models/phi.rs/0 | {
"file_path": "candle/candle-transformers/src/models/phi.rs",
"repo_id": "candle",
"token_count": 6064
} | 43 |
// Adapted from:
// https://github.com/ChaoningZhang/MobileSAM/blob/master/mobile_sam/modeling/tiny_vit_sam.py
use candle::{IndexOp, Result, Tensor, D};
use candle_nn::{Conv2dConfig, Module, VarBuilder};
const MBCONV_EXPAND_RATIO: usize = 4;
const MLP_RATIO: usize = 4;
const LOCAL_CONV_SIZE: usize = 3;
const IMG_SIZE:... | candle/candle-transformers/src/models/segment_anything/tiny_vit.rs/0 | {
"file_path": "candle/candle-transformers/src/models/segment_anything/tiny_vit.rs",
"repo_id": "candle",
"token_count": 10372
} | 44 |
use super::common::{AttnBlock, ResBlock, TimestepBlock};
use candle::{DType, Result, Tensor, D};
use candle_nn::VarBuilder;
#[derive(Debug)]
struct Block {
res_block: ResBlock,
ts_block: TimestepBlock,
attn_block: AttnBlock,
}
#[derive(Debug)]
pub struct WPrior {
projection: candle_nn::Conv2d,
con... | candle/candle-transformers/src/models/wuerstchen/prior.rs/0 | {
"file_path": "candle/candle-transformers/src/models/wuerstchen/prior.rs",
"repo_id": "candle",
"token_count": 1920
} | 45 |
use candle_transformers::models::bert;
use wasm_bindgen::prelude::*;
pub use bert::{BertModel, Config, DTYPE};
pub use tokenizers::{PaddingParams, Tokenizer};
#[wasm_bindgen]
extern "C" {
// Use `js_namespace` here to bind `console.log(..)` instead of just
// `log(..)`
#[wasm_bindgen(js_namespace = consol... | candle/candle-wasm-examples/bert/src/lib.rs/0 | {
"file_path": "candle/candle-wasm-examples/bert/src/lib.rs",
"repo_id": "candle",
"token_count": 226
} | 46 |
use crate::console_log;
use crate::worker::{ModelData, Worker, WorkerInput, WorkerOutput};
use std::str::FromStr;
use wasm_bindgen::prelude::*;
use wasm_bindgen_futures::JsFuture;
use yew::{html, Component, Context, Html};
use yew_agent::{Bridge, Bridged};
async fn fetch_url(url: &str) -> Result<Vec<u8>, JsValue> {
... | candle/candle-wasm-examples/llama2-c/src/app.rs/0 | {
"file_path": "candle/candle-wasm-examples/llama2-c/src/app.rs",
"repo_id": "candle",
"token_count": 5448
} | 47 |
//load Candle Bert Module wasm module
let init, ModelEncoder;
async function fetchArrayBuffer(url) {
const cacheName = "t5-candle-cache";
const cache = await caches.open(cacheName);
const cachedResponse = await cache.match(url);
if (cachedResponse) {
const data = await cachedResponse.arrayBuffer();
ret... | candle/candle-wasm-examples/t5/T5ModelEncoderWorker.js/0 | {
"file_path": "candle/candle-wasm-examples/t5/T5ModelEncoderWorker.js",
"repo_id": "candle",
"token_count": 873
} | 48 |
use candle_wasm_example_whisper::worker::{Decoder as D, ModelData};
use wasm_bindgen::prelude::*;
#[wasm_bindgen]
pub struct Decoder {
decoder: D,
}
#[wasm_bindgen]
impl Decoder {
#[wasm_bindgen(constructor)]
#[allow(clippy::too_many_arguments)]
pub fn new(
weights: Vec<u8>,
tokenizer:... | candle/candle-wasm-examples/whisper/src/bin/m.rs/0 | {
"file_path": "candle/candle-wasm-examples/whisper/src/bin/m.rs",
"repo_id": "candle",
"token_count": 694
} | 49 |
mod app;
pub mod coco_classes;
pub mod model;
pub mod worker;
pub use app::App;
pub use worker::Worker;
| candle/candle-wasm-examples/yolo/src/lib.rs/0 | {
"file_path": "candle/candle-wasm-examples/yolo/src/lib.rs",
"repo_id": "candle",
"token_count": 37
} | 50 |
module.exports = {
root: true,
parser: "@typescript-eslint/parser",
extends: [
"eslint:recommended",
"plugin:@typescript-eslint/recommended",
"plugin:svelte/recommended",
"prettier",
],
plugins: ["@typescript-eslint"],
ignorePatterns: ["*.cjs"],
overrides: [
{
files: ["*.svelte"],
parser: "svelte... | chat-ui/.eslintrc.cjs/0 | {
"file_path": "chat-ui/.eslintrc.cjs",
"repo_id": "chat-ui",
"token_count": 420
} | 51 |
## Privacy
> Last updated: April 15, 2024
Users of HuggingChat are authenticated through their HF user account.
We endorse Privacy by Design. As such, your conversations are private to you and will not be shared with anyone, including model authors, for any purpose, including for research or model training purposes.... | chat-ui/PRIVACY.md/0 | {
"file_path": "chat-ui/PRIVACY.md",
"repo_id": "chat-ui",
"token_count": 871
} | 52 |
# Common Issues
## 403：You don't have access to this conversation
Most likely you are running chat-ui over HTTP. The recommended option is to setup something like NGINX to handle HTTPS and proxy the requests to chat-ui. If you really need to run over HTTP you can add `ALLOW_INSECURE_COOKIES=true` to your `.env.local`... | chat-ui/docs/source/configuration/common-issues.md/0 | {
"file_path": "chat-ui/docs/source/configuration/common-issues.md",
"repo_id": "chat-ui",
"token_count": 118
} | 53 |
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