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# 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": 12419
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# coding=utf-8
# Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requir... | transformers/tests/models/longformer/test_modeling_longformer.py/0 | {
"file_path": "transformers/tests/models/longformer/test_modeling_longformer.py",
"repo_id": "transformers",
"token_count": 15701
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# coding=utf-8
# Copyright 2022 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | transformers/tests/models/mask2former/test_modeling_mask2former.py/0 | {
"file_path": "transformers/tests/models/mask2former/test_modeling_mask2former.py",
"repo_id": "transformers",
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# coding=utf-8
# Copyright 2024
#
# 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 to in writin... | transformers/tests/models/myt5/test_tokenization_myt5.py/0 | {
"file_path": "transformers/tests/models/myt5/test_tokenization_myt5.py",
"repo_id": "transformers",
"token_count": 3019
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# coding=utf-8
# Copyright 2022 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | transformers/tests/models/opt/test_modeling_tf_opt.py/0 | {
"file_path": "transformers/tests/models/opt/test_modeling_tf_opt.py",
"repo_id": "transformers",
"token_count": 7560
} |
# 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/patchtst/test_modeling_patchtst.py/0 | {
"file_path": "transformers/tests/models/patchtst/test_modeling_patchtst.py",
"repo_id": "transformers",
"token_count": 6859
} |
# coding=utf-8
# Copyright 2024 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/phi3/test_modeling_phi3.py/0 | {
"file_path": "transformers/tests/models/phi3/test_modeling_phi3.py",
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# coding=utf-8
# Copyright 2021 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | transformers/tests/models/rembert/test_modeling_tf_rembert.py/0 | {
"file_path": "transformers/tests/models/rembert/test_modeling_tf_rembert.py",
"repo_id": "transformers",
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# coding=utf-8
# Copyright 2022 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | transformers/tests/models/roc_bert/test_modeling_roc_bert.py/0 | {
"file_path": "transformers/tests/models/roc_bert/test_modeling_roc_bert.py",
"repo_id": "transformers",
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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/sam/test_modeling_sam.py/0 | {
"file_path": "transformers/tests/models/sam/test_modeling_sam.py",
"repo_id": "transformers",
"token_count": 14432
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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/seggpt/test_modeling_seggpt.py/0 | {
"file_path": "transformers/tests/models/seggpt/test_modeling_seggpt.py",
"repo_id": "transformers",
"token_count": 8380
} |
# coding=utf-8
# Copyright 2024 BigCode 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-2.0
... | transformers/tests/models/starcoder2/test_modeling_starcoder2.py/0 | {
"file_path": "transformers/tests/models/starcoder2/test_modeling_starcoder2.py",
"repo_id": "transformers",
"token_count": 9344
} |
# coding=utf-8
# Copyright 2023 The Intel Team Authors, 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/... | transformers/tests/models/tvp/test_modeling_tvp.py/0 | {
"file_path": "transformers/tests/models/tvp/test_modeling_tvp.py",
"repo_id": "transformers",
"token_count": 5921
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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/vivit/test_modeling_vivit.py/0 | {
"file_path": "transformers/tests/models/vivit/test_modeling_vivit.py",
"repo_id": "transformers",
"token_count": 6340
} |
# 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_with_lm/test_processor_wav2vec2_with_lm.py/0 | {
"file_path": "transformers/tests/models/wav2vec2_with_lm/test_processor_wav2vec2_with_lm.py",
"repo_id": "transformers",
"token_count": 9350
} |
# 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/xglm/test_tokenization_xglm.py/0 | {
"file_path": "transformers/tests/models/xglm/test_tokenization_xglm.py",
"repo_id": "transformers",
"token_count": 4238
} |
# 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/optimization/test_optimization_tf.py/0 | {
"file_path": "transformers/tests/optimization/test_optimization_tf.py",
"repo_id": "transformers",
"token_count": 1782
} |
# 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": 3521
} |
# 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": 5255
} |
# 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/eetq_integration/test_eetq.py/0 | {
"file_path": "transformers/tests/quantization/eetq_integration/test_eetq.py",
"repo_id": "transformers",
"token_count": 2636
} |
import os
import sys
import unittest
ROOT_DIR = os.path.dirname(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(ROOT_DIR, "utils"))
import create_dependency_mapping # noqa: E402
# This is equivalent to `all` in the current library state (as of 09/01/2025)
MODEL_ROOT = os.... | transformers/tests/repo_utils/modular/test_conversion_order.py/0 | {
"file_path": "transformers/tests/repo_utils/modular/test_conversion_order.py",
"repo_id": "transformers",
"token_count": 1422
} |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggingface imp... | transformers/tests/sagemaker/test_multi_node_model_parallel.py/0 | {
"file_path": "transformers/tests/sagemaker/test_multi_node_model_parallel.py",
"repo_id": "transformers",
"token_count": 2103
} |
# coding=utf-8
# Copyright 2018 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 a... | transformers/tests/tokenization/test_tokenization_utils.py/0 | {
"file_path": "transformers/tests/tokenization/test_tokenization_utils.py",
"repo_id": "transformers",
"token_count": 9216
} |
# 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
} |
# 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
} |
# 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_tokenization_utils.py/0 | {
"file_path": "transformers/tests/utils/test_tokenization_utils.py",
"repo_id": "transformers",
"token_count": 5858
} |
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable... | transformers/utils/check_repo.py/0 | {
"file_path": "transformers/utils/check_repo.py",
"repo_id": "transformers",
"token_count": 20316
} |
# 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/update_tiny_models.py/0 | {
"file_path": "transformers/utils/update_tiny_models.py",
"repo_id": "transformers",
"token_count": 3071
} |
# Data Utilities
## is_conversational
[[autodoc]] is_conversational
## apply_chat_template
[[autodoc]] apply_chat_template
## maybe_apply_chat_template
[[autodoc]] maybe_apply_chat_template
## extract_prompt
[[autodoc]] extract_prompt
## maybe_extract_prompt
[[autodoc]] maybe_extract_prompt
## unpair_prefere... | trl/docs/source/data_utils.md/0 | {
"file_path": "trl/docs/source/data_utils.md",
"repo_id": "trl",
"token_count": 188
} |
# Supervised Fine-tuning Trainer
[](https://huggingface.co/models?other=sft,trl) [](https://github.com/huggingface/smol-course/tree/main/1_instruction_tuning)
Supervised fine-tuning (or SFT for short) is... | trl/docs/source/sft_trainer.md/0 | {
"file_path": "trl/docs/source/sft_trainer.md",
"repo_id": "trl",
"token_count": 11435
} |
# 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/lm-human-preferences-descriptiveness.py/0 | {
"file_path": "trl/examples/datasets/lm-human-preferences-descriptiveness.py",
"repo_id": "trl",
"token_count": 1687
} |
# 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/reward_modeling.py/0 | {
"file_path": "trl/examples/research_projects/stack_llama/scripts/reward_modeling.py",
"repo_id": "trl",
"token_count": 4691
} |
# 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
} |
# 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": 27027
} |
# 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_rich_progress_callback.py/0 | {
"file_path": "trl/tests/test_rich_progress_callback.py",
"repo_id": "trl",
"token_count": 986
} |
# 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
} |
# 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/sft.py/0 | {
"file_path": "trl/trl/scripts/sft.py",
"repo_id": "trl",
"token_count": 1589
} |
# 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_trainer.py/0 | {
"file_path": "trl/trl/trainer/gkd_trainer.py",
"repo_id": "trl",
"token_count": 7522
} |
# 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/prm_config.py/0 | {
"file_path": "trl/trl/trainer/prm_config.py",
"repo_id": "trl",
"token_count": 1315
} |
# FP8 Benchmarks
Comparing and running [TransformerEngine](https://github.com/NVIDIA/TransformerEngine) FP8 with accelerate
## Overview
This repo provides scripts which compare native TransformerEngine model training against `accelerate`'s own integration. Each modeling type is segmented out via a script, supporting... | accelerate/benchmarks/fp8/transformer_engine/README.md/0 | {
"file_path": "accelerate/benchmarks/fp8/transformer_engine/README.md",
"repo_id": "accelerate",
"token_count": 326
} |
<!--Copyright 2022 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | accelerate/docs/source/basic_tutorials/migration.md/0 | {
"file_path": "accelerate/docs/source/basic_tutorials/migration.md",
"repo_id": "accelerate",
"token_count": 3069
} |
<!--Copyright 2022 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | accelerate/docs/source/index.md/0 | {
"file_path": "accelerate/docs/source/index.md",
"repo_id": "accelerate",
"token_count": 1354
} |
<!--Copyright 2021 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | accelerate/docs/source/quicktour.md/0 | {
"file_path": "accelerate/docs/source/quicktour.md",
"repo_id": "accelerate",
"token_count": 3047
} |
<!--
Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agree... | accelerate/docs/source/usage_guides/profiler.md/0 | {
"file_path": "accelerate/docs/source/usage_guides/profiler.md",
"repo_id": "accelerate",
"token_count": 5179
} |
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | accelerate/examples/inference/pippy/llama.py/0 | {
"file_path": "accelerate/examples/inference/pippy/llama.py",
"repo_id": "accelerate",
"token_count": 768
} |
#!/usr/bin/env python
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unles... | accelerate/src/accelerate/commands/config/__init__.py/0 | {
"file_path": "accelerate/src/accelerate/commands/config/__init__.py",
"repo_id": "accelerate",
"token_count": 516
} |
# 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 | {
"file_path": "accelerate/src/accelerate/commands/menu/selection_menu.py",
"repo_id": "accelerate",
"token_count": 2187
} |
#!/usr/bin/env python
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unles... | accelerate/src/accelerate/test_utils/examples.py/0 | {
"file_path": "accelerate/src/accelerate/test_utils/examples.py",
"repo_id": "accelerate",
"token_count": 2735
} |
#!/usr/bin/env python
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unles... | accelerate/src/accelerate/test_utils/scripts/test_script.py/0 | {
"file_path": "accelerate/src/accelerate/test_utils/scripts/test_script.py",
"repo_id": "accelerate",
"token_count": 13893
} |
# 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/modeling.py/0 | {
"file_path": "accelerate/src/accelerate/utils/modeling.py",
"repo_id": "accelerate",
"token_count": 38832
} |
# 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/fsdp/test_fsdp.py/0 | {
"file_path": "accelerate/tests/fsdp/test_fsdp.py",
"repo_id": "accelerate",
"token_count": 9529
} |
# 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
} |
# 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": 8972
} |
# Changelog
This documents the main changes to the `candle` crate.
## v0.3.1 - Unreleased
### Added
### Modified
## v0.3.0 - 2023-10-01
### Added
- Added the Mistral 7b v0.1 model
[983](https://github.com/huggingface/candle/pull/983).
- Quantized version of the Mistral model
[1009](https://github.com/huggingf... | candle/CHANGELOG.md/0 | {
"file_path": "candle/CHANGELOG.md",
"repo_id": "candle",
"token_count": 1525
} |
# MNIST
So we now have downloaded the MNIST parquet files, let's put them in a simple struct.
```rust,ignore
{{#include ../lib.rs:book_training_3}}
```
The parsing of the file and putting it into single tensors requires the dataset to fit the entire memory.
It is quite rudimentary, but simple enough for a small data... | candle/candle-book/src/training/mnist.md/0 | {
"file_path": "candle/candle-book/src/training/mnist.md",
"repo_id": "candle",
"token_count": 93
} |
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, c: &Tensor) {
a.where_cond(b, c).unwrap();
}
const fn create_cond_arr<const N: usize>() -> ... | candle/candle-core/benches/benchmarks/where_cond.rs/0 | {
"file_path": "candle/candle-core/benches/benchmarks/where_cond.rs",
"repo_id": "candle",
"token_count": 939
} |
//! Implementation of Backend Fns for CPU
use crate::backend::{BackendDevice, BackendStorage};
use crate::op::{BinaryOpT, CmpOp, ReduceOp, UnaryOpT};
use crate::{DType, Error, IntDType, Layout, Result, Shape, WithDType};
use half::{bf16, f16};
use rayon::prelude::*;
mod utils;
pub use utils::{
binary_map, binary_m... | candle/candle-core/src/cpu_backend/mod.rs/0 | {
"file_path": "candle/candle-core/src/cpu_backend/mod.rs",
"repo_id": "candle",
"token_count": 64089
} |
//! ML framework for Rust
//!
//! ```rust
//! use candle_core::{Tensor, DType, Device};
//! # use candle_core::Error;
//! # fn main() -> Result<(), Error>{
//!
//! let a = Tensor::arange(0f32, 6f32, &Device::Cpu)?.reshape((2, 3))?;
//! let b = Tensor::arange(0f32, 12f32, &Device::Cpu)?.reshape((3, 4))?;
//! let c = a.m... | candle/candle-core/src/lib.rs/0 | {
"file_path": "candle/candle-core/src/lib.rs",
"repo_id": "candle",
"token_count": 1894
} |
use super::k_quants::{
BlockQ2K, BlockQ3K, BlockQ4K, BlockQ4_0, BlockQ5K, BlockQ6K, BlockQ8K, BlockQ8_0, QK8_0, QK_K,
};
use crate::Result;
use byteorder::{ByteOrder, LittleEndian};
#[allow(unused_imports)]
#[cfg(target_arch = "arm")]
use core::arch::arm::*;
#[allow(unused_imports)]
#[cfg(target_arch = "aarch64")... | candle/candle-core/src/quantized/neon.rs/0 | {
"file_path": "candle/candle-core/src/quantized/neon.rs",
"repo_id": "candle",
"token_count": 15290
} |
use candle_core::backend::BackendStorage;
use candle_core::cpu_backend;
use candle_core::test_utils::to_vec1_round;
use candle_core::{CpuStorage, CustomOp1, DType, Device, Error, Layout, Result, Shape, Tensor};
fn fwd<T: num_traits::Float>(v: T, alpha: f64) -> T {
if v.is_sign_positive() {
v
} else {
... | candle/candle-core/tests/custom_op_tests.rs/0 | {
"file_path": "candle/candle-core/tests/custom_op_tests.rs",
"repo_id": "candle",
"token_count": 2721
} |
use anyhow::{Error as E, Result};
use candle::{DType, Device, Tensor};
use candle_nn::VarBuilder;
use candle_transformers::models::colpali::Model;
use candle_transformers::models::{colpali, paligemma};
use clap::Parser;
use hf_hub::{api::sync::Api, Repo, RepoType};
use image::DynamicImage;
use pdf2image::{RenderOptions... | candle/candle-examples/examples/colpali/main.rs/0 | {
"file_path": "candle/candle-examples/examples/colpali/main.rs",
"repo_id": "candle",
"token_count": 3864
} |
# candle-flux: image generation with latent rectified flow transformers
Flux is a 12B rectified flow transformer capable of generating images from text
descriptions,
[huggingface](https://huggingface.co/black-forest-labs/FLUX.1-schnell),
[github](https://github... | candle/candle-examples/examples/flux/README.md/0 | {
"file_path": "candle/candle-examples/examples/flux/README.md",
"repo_id": "candle",
"token_count": 216
} |
# candle-jina-bert
Jina-Bert is a general large language model with a context size of 8192, [model
card](https://huggingface.co/jinaai/jina-embeddings-v2-base-en). In this example
it can be used for two different tasks:
- Compute sentence embeddings for a prompt.
- Compute similarities between a set of sentences.
##... | candle/candle-examples/examples/jina-bert/README.md/0 | {
"file_path": "candle/candle-examples/examples/jina-bert/README.md",
"repo_id": "candle",
"token_count": 663
} |
# candle-mobilenetv4
[MobileNetV4 - Universal Models for the Mobile Ecosystem](https://arxiv.org/abs/2404.10518)
This candle implementation uses pre-trained MobileNetV4 models from timm for inference.
The classification head has been trained on the ImageNet dataset and returns the probabilities for the top-5 classes.
... | candle/candle-examples/examples/mobilenetv4/README.md/0 | {
"file_path": "candle/candle-examples/examples/mobilenetv4/README.md",
"repo_id": "candle",
"token_count": 248
} |
use anyhow::Result;
use candle::{Device, Tensor};
use clap::{Parser, Subcommand};
#[derive(Subcommand, Debug, Clone)]
enum Command {
Print {
#[arg(long)]
file: String,
},
SimpleEval {
#[arg(long)]
file: String,
},
}
#[derive(Parser, Debug)]
#[command(author, version, a... | candle/candle-examples/examples/onnx_basics.rs/0 | {
"file_path": "candle/candle-examples/examples/onnx_basics.rs",
"repo_id": "candle",
"token_count": 2016
} |
# candle-repvgg
[RepVGG: Making VGG-style ConvNets Great Again](https://arxiv.org/abs/2101.03697).
This candle implementation uses a pre-trained RepVGG network for inference. The
classification head has been trained on the ImageNet dataset and returns the
probabilities for the top-5 classes.
## Running an example
`... | candle/candle-examples/examples/repvgg/README.md/0 | {
"file_path": "candle/candle-examples/examples/repvgg/README.md",
"repo_id": "candle",
"token_count": 254
} |
# 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 | {
"file_path": "candle/candle-examples/examples/whisper/README.md",
"repo_id": "candle",
"token_count": 627
} |
[net]
# Testing
batch=1
subdivisions=1
# Training
# batch=64
# subdivisions=16
width= 416
height = 416
channels=3
momentum=0.9
decay=0.0005
angle=0
saturation = 1.5
exposure = 1.5
hue=.1
learning_rate=0.001
burn_in=1000
max_batches = 500200
policy=steps
steps=400000,450000
scales=.1,.1
[convolutional]
batch_normaliz... | candle/candle-examples/examples/yolo-v3/yolo-v3.cfg/0 | {
"file_path": "candle/candle-examples/examples/yolo-v3/yolo-v3.cfg",
"repo_id": "candle",
"token_count": 3586
} |
[package]
name = "candle-flash-attn"
version = "0.8.2"
edition = "2021"
description = "Flash attention layer for the candle ML framework."
repository = "https://github.com/huggingface/candle"
keywords = ["blas", "tensor", "machine-learning"]
categories = ["science"]
license = "MIT OR Apache-2.0"
readme = "README.md"
... | candle/candle-flash-attn/Cargo.toml/0 | {
"file_path": "candle/candle-flash-attn/Cargo.toml",
"repo_id": "candle",
"token_count": 266
} |
/******************************************************************************
* Copyright (c) 2024, Tri Dao.
******************************************************************************/
#pragma once
#include <cute/tensor.hpp>
namespace flash {
using namespace cute;
template <typename Engine, typename Layout... | candle/candle-flash-attn/kernels/mask.h/0 | {
"file_path": "candle/candle-flash-attn/kernels/mask.h",
"repo_id": "candle",
"token_count": 6255
} |
#include "cuda_fp16.h"
#include "cuda_bf16.h"
// Table showing which features are supported on which compute capability
// https://docs.nvidia.com/cuda/cuda-c-programming-guide/#features-and-technical-specifications
// FIXME: the minimum compute capabilities are just guesses since the table is not specific enough
#i... | candle/candle-kernels/src/compatibility.cuh/0 | {
"file_path": "candle/candle-kernels/src/compatibility.cuh",
"repo_id": "candle",
"token_count": 2734
} |
#include <metal_stdlib>
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 < num_dims; d++) {
uint dim_idx = num_dims - 1 - d;
strided_i += (idx % dims[dim_idx]) * str... | candle/candle-metal-kernels/src/cast.metal/0 | {
"file_path": "candle/candle-metal-kernels/src/cast.metal",
"repo_id": "candle",
"token_count": 2045
} |
#include <metal_stdlib>
#include <metal_math>
#
using namespace metal;
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 < num_dims; d++) {
uint dim_idx = num_dims - 1 - d;
... | candle/candle-metal-kernels/src/unary.metal/0 | {
"file_path": "candle/candle-metal-kernels/src/unary.metal",
"repo_id": "candle",
"token_count": 2665
} |
//! Activation Functions
//!
use candle::{Result, Tensor};
#[derive(Debug, Clone, Copy, PartialEq, serde::Deserialize, serde::Serialize, Default)]
#[serde(rename_all = "lowercase")]
pub enum Activation {
#[default]
#[serde(alias = "gelu")]
Gelu,
#[serde(alias = "gelu_new")]
NewGelu,
Relu,
R... | candle/candle-nn/src/activation.rs/0 | {
"file_path": "candle/candle-nn/src/activation.rs",
"repo_id": "candle",
"token_count": 1665
} |
//! Rotary Embeddings
//!
use candle::{CpuStorage, Layout, Result, Shape, Tensor, D};
use rayon::prelude::*;
/// Interleaved variant of rotary embeddings.
/// The x0 and x1 value are interleaved on the n_embd (= head_dim) dimension.
/// The resulting y0 and y1 are also interleaved with:
/// y0 = x0*cos - x1*sin
/// ... | candle/candle-nn/src/rotary_emb.rs/0 | {
"file_path": "candle/candle-nn/src/rotary_emb.rs",
"repo_id": "candle",
"token_count": 15521
} |
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
} |
# 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
} |
use candle::{Result, Tensor, D};
use candle_nn::{conv2d, group_norm, Conv2d, GroupNorm, VarBuilder};
// https://github.com/black-forest-labs/flux/blob/727e3a71faf37390f318cf9434f0939653302b60/src/flux/modules/autoencoder.py#L9
#[derive(Debug, Clone)]
pub struct Config {
pub resolution: usize,
pub in_channels: ... | candle/candle-transformers/src/models/flux/autoencoder.rs/0 | {
"file_path": "candle/candle-transformers/src/models/flux/autoencoder.rs",
"repo_id": "candle",
"token_count": 7145
} |
//! The LLaVA (Large Language and Vision Assistant) model.
//!
//! This provides the main model implementation combining a vision tower (CLIP) with
//! language model (Llama) for multimodal capabilities. The architecture implements the training-free projection technique.
//!
//! - 💻[GH Link](https://github.com/haotian... | candle/candle-transformers/src/models/llava/mod.rs/0 | {
"file_path": "candle/candle-transformers/src/models/llava/mod.rs",
"repo_id": "candle",
"token_count": 8610
} |
//! Mix of Multi-scale Dilated and Traditional Convolutions
//!
//! Mix of Multi-scale Dilated and Traditional Convolutions (MMDiT) is an architecture
//! introduced for Stable Diffusion 3, with the MMDiT-X variant used in Stable Diffusion 3.5.
//!
//! - 📝 [Research Paper](https://arxiv.org/abs/2403.03206)
//! - 💻 Co... | candle/candle-transformers/src/models/mmdit/mod.rs/0 | {
"file_path": "candle/candle-transformers/src/models/mmdit/mod.rs",
"repo_id": "candle",
"token_count": 395
} |
//! Multimodal multi-purpose model combining Gemma-based language model with SigLIP image understanding
//!
//! See PaLiGemma details at:
//! - [Paper](https://arxiv.org/abs/2402.05257)
//! - [Google Blog Post](https://blog.research.google/2024/02/paligemma-scaling-language-image.html)
//!
//! The model is a multimodal... | candle/candle-transformers/src/models/paligemma.rs/0 | {
"file_path": "candle/candle-transformers/src/models/paligemma.rs",
"repo_id": "candle",
"token_count": 2807
} |
//! Quantized MPT model implementation.
//!
//! MPT (MPT-7B) is a causal transformer model series optimized for code generation.
//! This implementation provides quantization for reduced memory and compute.
//!
//! Key characteristics:
//! - Multi-Query Grouped Attention (MQA)
//! - Support for KV-caching
//! - Pre-com... | candle/candle-transformers/src/models/quantized_mpt.rs/0 | {
"file_path": "candle/candle-transformers/src/models/quantized_mpt.rs",
"repo_id": "candle",
"token_count": 3969
} |
//! Segformer model implementation for semantic segmentation and image classification.
//!
//! Segformer is a transformer-based model designed for vision tasks. It uses a hierarchical
//! structure that progressively generates features at different scales.
//!
//! Key characteristics:
//! - Efficient self-attention wit... | candle/candle-transformers/src/models/segformer.rs/0 | {
"file_path": "candle/candle-transformers/src/models/segformer.rs",
"repo_id": "candle",
"token_count": 11540
} |
//! ResNet Building Blocks
//!
//! Some Residual Network blocks used in UNet models.
//!
//! Denoising Diffusion Implicit Models, K. He and al, 2015.
//! - [Paper](https://arxiv.org/abs/1512.03385)
//!
use crate::models::with_tracing::{conv2d, Conv2d};
use candle::{Result, Tensor, D};
use candle_nn as nn;
use candle_nn... | candle/candle-transformers/src/models/stable_diffusion/resnet.rs/0 | {
"file_path": "candle/candle-transformers/src/models/stable_diffusion/resnet.rs",
"repo_id": "candle",
"token_count": 2292
} |
use super::Config;
use crate::models::with_tracing::{linear, linear_no_bias, Linear};
use candle::{Device, IndexOp, Result, Tensor, D};
use candle_nn::{embedding, Conv1d, Conv1dConfig, Embedding, LayerNorm, Module, VarBuilder};
fn conv1d(
in_channels: usize,
out_channels: usize,
kernel_size: usize,
con... | candle/candle-transformers/src/models/whisper/model.rs/0 | {
"file_path": "candle/candle-transformers/src/models/whisper/model.rs",
"repo_id": "candle",
"token_count": 7050
} |
//! Varbuilder for Loading gguf files
//!
//! VarBuilder is a utility to store quantized tensors from a [GGUF model file](https://huggingface.co/docs/hub/gguf).
//! These tensors can be loaded from disk using `from_gguf` or from an in-memory
//! buffer using `from_gguf_buffer`.
use candle::quantized::QTensor;
use cand... | candle/candle-transformers/src/quantized_var_builder.rs/0 | {
"file_path": "candle/candle-transformers/src/quantized_var_builder.rs",
"repo_id": "candle",
"token_count": 1649
} |
<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<style>
@import url("https://fonts.googleapis.com/css2?family=Source+Code+Pro:wght@200;300;400&family=Source+Sans+3:wght@100;200;300;400;500;600;700;800;900&display=swap");... | candle/candle-wasm-examples/blip/index.html/0 | {
"file_path": "candle/candle-wasm-examples/blip/index.html",
"repo_id": "candle",
"token_count": 7164
} |
use crate::model::{Cache, Config, Llama};
use byteorder::{LittleEndian, ReadBytesExt};
use candle::{DType, Device, IndexOp, Result, Shape, Tensor};
use candle_nn::VarBuilder;
use candle_transformers::generation::LogitsProcessor;
use serde::{Deserialize, Serialize};
use tokenizers::Tokenizer;
use wasm_bindgen::prelude::... | candle/candle-wasm-examples/llama2-c/src/worker.rs/0 | {
"file_path": "candle/candle-wasm-examples/llama2-c/src/worker.rs",
"repo_id": "candle",
"token_count": 5770
} |
export async function extractEmbeddings(
worker,
weightsURL,
tokenizerURL,
configURL,
modelID,
sentences,
updateStatus,
normalize_embeddings = true
) {
return new Promise((resolve, reject) => {
worker.postMessage({
weightsURL,
tokenizerURL,
configURL,
modelID,
sentenc... | candle/candle-wasm-examples/t5/utils.js/0 | {
"file_path": "candle/candle-wasm-examples/t5/utils.js",
"repo_id": "candle",
"token_count": 2339
} |
[package]
name = "candle-wasm-example-yolo"
version.workspace = true
edition.workspace = true
description.workspace = true
repository.workspace = true
keywords.workspace = true
categories.workspace = true
license.workspace = true
[dependencies]
candle = { workspace = true }
candle-nn = { workspace = true }
num-traits ... | candle/candle-wasm-examples/yolo/Cargo.toml/0 | {
"file_path": "candle/candle-wasm-examples/yolo/Cargo.toml",
"repo_id": "candle",
"token_count": 464
} |
pub fn add(left: usize, right: usize) -> usize {
left + right
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn it_works() {
let result = add(2, 2);
assert_eq!(result, 4);
}
}
| candle/candle-wasm-tests/src/lib.rs/0 | {
"file_path": "candle/candle-wasm-tests/src/lib.rs",
"repo_id": "candle",
"token_count": 108
} |
image:
repository: huggingface
name: chat-ui
nodeSelector:
role-huggingchat: "true"
tolerations:
- key: "huggingface.co/huggingchat"
operator: "Equal"
value: "true"
effect: "NoSchedule"
serviceAccount:
enabled: true
create: true
name: huggingchat-prod
ingress:
path: "/chat"
annotations... | chat-ui/chart/env/prod.yaml/0 | {
"file_path": "chat-ui/chart/env/prod.yaml",
"repo_id": "chat-ui",
"token_count": 11587
} |
# Multimodal
We currently support [IDEFICS](https://huggingface.co/blog/idefics) (hosted on [TGI](./providers/tgi)), OpenAI and Anthropic Claude 3 as multimodal models. You can enable it by setting `multimodal: true` in your `MODELS` configuration. For IDEFICS, you must have a [PRO HF Api token](https://huggingface.co... | chat-ui/docs/source/configuration/models/multimodal.md/0 | {
"file_path": "chat-ui/docs/source/configuration/models/multimodal.md",
"repo_id": "chat-ui",
"token_count": 439
} |
# Web Search
Chat UI features a powerful Web Search feature. A high level overview of how it works:
1. Generate an appropriate search query from the user prompt using the `TASK_MODEL`
2. Perform web search via an external provider (i.e. Serper) or via locally scrape Google results
3. Load each search result into play... | chat-ui/docs/source/configuration/web-search.md/0 | {
"file_path": "chat-ui/docs/source/configuration/web-search.md",
"repo_id": "chat-ui",
"token_count": 838
} |
/// <reference types="@sveltejs/kit" />
/// <reference types="unplugin-icons/types/svelte" />
import type { User } from "$lib/types/User";
// See https://kit.svelte.dev/docs/types#app
// for information about these interfaces
declare global {
namespace App {
// interface Error {}
interface Locals {
sessionId:... | chat-ui/src/app.d.ts/0 | {
"file_path": "chat-ui/src/app.d.ts",
"repo_id": "chat-ui",
"token_count": 190
} |
<script lang="ts">
import { base } from "$app/paths";
import { page } from "$app/state";
import { env as envPublic } from "$env/dynamic/public";
import LogoHuggingFaceBorderless from "$lib/components/icons/LogoHuggingFaceBorderless.svelte";
import Modal from "$lib/components/Modal.svelte";
import { useSettingsSto... | chat-ui/src/lib/components/LoginModal.svelte/0 | {
"file_path": "chat-ui/src/lib/components/LoginModal.svelte",
"repo_id": "chat-ui",
"token_count": 941
} |
<script lang="ts">
import { fade } from "svelte/transition";
import Portal from "./Portal.svelte";
import IconDazzled from "$lib/components/icons/IconDazzled.svelte";
interface Props {
message?: string;
}
let { message = "" }: Props = $props();
</script>
<Portal>
<div
transition:fade|global={{ duration: 3... | chat-ui/src/lib/components/Toast.svelte/0 | {
"file_path": "chat-ui/src/lib/components/Toast.svelte",
"repo_id": "chat-ui",
"token_count": 337
} |
<script lang="ts">
import { invalidateAll } from "$app/navigation";
import { page } from "$app/state";
import { base } from "$app/paths";
import type { Model } from "$lib/types/Model";
interface Props {
models: Model[];
currentModel: Model;
}
let { models, currentModel }: Props = $props();
let selectedMo... | chat-ui/src/lib/components/chat/ModelSwitch.svelte/0 | {
"file_path": "chat-ui/src/lib/components/chat/ModelSwitch.svelte",
"repo_id": "chat-ui",
"token_count": 640
} |
import type { Migration } from ".";
import { collections } from "$lib/server/database";
import { ObjectId } from "mongodb";
import { ReviewStatus } from "$lib/types/Review";
const updateFeaturedToReview: Migration = {
_id: new ObjectId("000000000000000000000008"),
name: "Update featured to review",
up: async () => ... | chat-ui/src/lib/migrations/routines/08-update-featured-to-review.ts/0 | {
"file_path": "chat-ui/src/lib/migrations/routines/08-update-featured-to-review.ts",
"repo_id": "chat-ui",
"token_count": 326
} |
import { buildPrompt } from "$lib/buildPrompt";
import { textGenerationStream } from "@huggingface/inference";
import { z } from "zod";
import type { Endpoint } from "../endpoints";
export const endpointAwsParametersSchema = z.object({
weight: z.number().int().positive().default(1),
model: z.any(),
type: z.literal(... | chat-ui/src/lib/server/endpoints/aws/endpointAws.ts/0 | {
"file_path": "chat-ui/src/lib/server/endpoints/aws/endpointAws.ts",
"repo_id": "chat-ui",
"token_count": 695
} |
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