text stringlengths 7 324k | id stringlengths 14 166 | metadata dict | __index_level_0__ int64 0 463 |
|---|---|---|---|
# Copyright 2020 The HuggingFace Datasets Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ... | datasets/metrics/coval/coval.py/0 | {
"file_path": "datasets/metrics/coval/coval.py",
"repo_id": "datasets",
"token_count": 5731
} | 66 |
# Metric Card for MAE
## Metric Description
Mean Absolute Error (MAE) is the mean of the magnitude of difference between the predicted and actual numeric values:
## How to Use
At minimum, this metric re... | datasets/metrics/mae/README.md/0 | {
"file_path": "datasets/metrics/mae/README.md",
"repo_id": "datasets",
"token_count": 1421
} | 67 |
# Metric Card for Perplexity
## Metric Description
Given a model and an input text sequence, perplexity measures how likely the model is to generate the input text sequence. This can be used in two main ways:
1. to evaluate how well the model has learned the distribution of the text it was trained on
- In this cas... | datasets/metrics/perplexity/README.md/0 | {
"file_path": "datasets/metrics/perplexity/README.md",
"repo_id": "datasets",
"token_count": 1345
} | 68 |
# Metric Card for Spearman Correlation Coefficient Metric (spearmanr)
## Metric Description
The Spearman rank-order correlation coefficient is a measure of the
relationship between two datasets. Like other correlation coefficients,
this one varies between -1 and +1 with 0 implying no correlation.
Positive correlation... | datasets/metrics/spearmanr/README.md/0 | {
"file_path": "datasets/metrics/spearmanr/README.md",
"repo_id": "datasets",
"token_count": 1585
} | 69 |
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# 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.... | datasets/metrics/wiki_split/wiki_split.py/0 | {
"file_path": "datasets/metrics/wiki_split/wiki_split.py",
"repo_id": "datasets",
"token_count": 5827
} | 70 |
import os
import re
import shutil
from argparse import ArgumentParser, Namespace
from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger
HIGHLIGHT_MESSAGE_PRE = """<<<<<<< This should probably be modified because it mentions: """
HIGHLIGHT_MESSAGE_POST = """=======
>>>>>>>... | datasets/src/datasets/commands/convert.py/0 | {
"file_path": "datasets/src/datasets/commands/convert.py",
"repo_id": "datasets",
"token_count": 3822
} | 71 |
# ruff: noqa
__all__ = [
"Audio",
"Array2D",
"Array3D",
"Array4D",
"Array5D",
"ClassLabel",
"Features",
"Sequence",
"Value",
"Image",
"Translation",
"TranslationVariableLanguages",
]
from .audio import Audio
from .features import Array2D, Array3D, Array4D, Array5D, Class... | datasets/src/datasets/features/__init__.py/0 | {
"file_path": "datasets/src/datasets/features/__init__.py",
"repo_id": "datasets",
"token_count": 165
} | 72 |
# Copyright 2020 The HuggingFace Datasets Authors and the TensorFlow Datasets Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# U... | datasets/src/datasets/info.py/0 | {
"file_path": "datasets/src/datasets/info.py",
"repo_id": "datasets",
"token_count": 11409
} | 73 |
import inspect
import re
from typing import Dict, List, Tuple
from huggingface_hub.utils import insecure_hashlib
from .arrow import arrow
from .audiofolder import audiofolder
from .cache import cache # noqa F401
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pand... | datasets/src/datasets/packaged_modules/__init__.py/0 | {
"file_path": "datasets/src/datasets/packaged_modules/__init__.py",
"repo_id": "datasets",
"token_count": 1108
} | 74 |
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
logger = datasets.utils.logging.get_logger(__name__)
@dataclass
... | datasets/src/datasets/packaged_modules/json/json.py/0 | {
"file_path": "datasets/src/datasets/packaged_modules/json/json.py",
"repo_id": "datasets",
"token_count": 5320
} | 75 |
import importlib.util
import os
import tempfile
from pathlib import PurePath
from typing import TYPE_CHECKING, Dict, List, NamedTuple, Optional, Union
import fsspec
import numpy as np
from .utils import logging
from .utils import tqdm as hf_tqdm
if TYPE_CHECKING:
from .arrow_dataset import Dataset # noqa: F401... | datasets/src/datasets/search.py/0 | {
"file_path": "datasets/src/datasets/search.py",
"repo_id": "datasets",
"token_count": 15237
} | 76 |
#!/usr/bin/env python
# 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/LI... | datasets/src/datasets/utils/_filelock.py/0 | {
"file_path": "datasets/src/datasets/utils/_filelock.py",
"repo_id": "datasets",
"token_count": 903
} | 77 |
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# 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.... | datasets/templates/new_dataset_script.py/0 | {
"file_path": "datasets/templates/new_dataset_script.py",
"repo_id": "datasets",
"token_count": 3156
} | 78 |
import contextlib
import os
import sqlite3
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy
def _check_sql_dataset(dataset, expected_f... | datasets/tests/io/test_sql.py/0 | {
"file_path": "datasets/tests/io/test_sql.py",
"repo_id": "datasets",
"token_count": 1628
} | 79 |
import importlib
import os
import tempfile
import types
from contextlib import nullcontext as does_not_raise
from multiprocessing import Process
from pathlib import Path
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from... | datasets/tests/test_builder.py/0 | {
"file_path": "datasets/tests/test_builder.py",
"repo_id": "datasets",
"token_count": 26111
} | 80 |
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize("dataset_size", [None, 400 * 2**20, 600 * 2**20])
@pytest.mark.parametrize("input_in_memory_max_size", ["default", 0, 100 * 2**20, 900 * 2**20])
def test_is_small_dataset(dataset_size, input_in_memory... | datasets/tests/test_info_utils.py/0 | {
"file_path": "datasets/tests/test_info_utils.py",
"repo_id": "datasets",
"token_count": 366
} | 81 |
import copy
import pickle
from typing import List, Union
import numpy as np
import pyarrow as pa
import pytest
from datasets import Sequence, Value
from datasets.features.features import Array2D, Array2DExtensionType, ClassLabel, Features, Image, get_nested_type
from datasets.table import (
ConcatenationTable,
... | datasets/tests/test_table.py/0 | {
"file_path": "datasets/tests/test_table.py",
"repo_id": "datasets",
"token_count": 21863
} | 82 |
<jupyter_start><jupyter_text>Unit 1: Train your first Deep Reinforcement Learning Agent 🤖In this notebook, you'll train your **first Deep Reinforcement Learning agent** a Lunar Lander agent that will learn to **land correctly on the Moon 🌕**. Using [Stable-Baselines3](https://stable-baselines3.readthedocs.io/en/maste... | deep-rl-class/notebooks/unit1/unit1.ipynb/0 | {
"file_path": "deep-rl-class/notebooks/unit1/unit1.ipynb",
"repo_id": "deep-rl-class",
"token_count": 7618
} | 83 |
# Welcome to the 🤗 Deep Reinforcement Learning Course [[introduction]]
<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit0/thumbnail.jpg" alt="Deep RL Course thumbnail" width="100%"/>
Welcome to the most fascinating topic in Artificial Intelligence: **Deep Reinfor... | deep-rl-class/units/en/unit0/introduction.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit0/introduction.mdx",
"repo_id": "deep-rl-class",
"token_count": 2554
} | 84 |
# The Bellman Equation: simplify our value estimation [[bellman-equation]]
The Bellman equation **simplifies our state value or state-action value calculation.**
<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit3/bellman.jpg" alt="Bellman equation"/>
With what w... | deep-rl-class/units/en/unit2/bellman-equation.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit2/bellman-equation.mdx",
"repo_id": "deep-rl-class",
"token_count": 1247
} | 85 |
# The Deep Q-Learning Algorithm [[deep-q-algorithm]]
We learned that Deep Q-Learning **uses a deep neural network to approximate the different Q-values for each possible action at a state** (value-function estimation).
The difference is that, during the training phase, instead of updating the Q-value of a state-actio... | deep-rl-class/units/en/unit3/deep-q-algorithm.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit3/deep-q-algorithm.mdx",
"repo_id": "deep-rl-class",
"token_count": 2281
} | 86 |
# What are the policy-based methods?
The main goal of Reinforcement learning is to **find the optimal policy \\(\pi^{*}\\) that will maximize the expected cumulative reward**.
Because Reinforcement Learning is based on the *reward hypothesis*: **all goals can be described as the maximization of the expected cumulative... | deep-rl-class/units/en/unit4/what-are-policy-based-methods.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit4/what-are-policy-based-methods.mdx",
"repo_id": "deep-rl-class",
"token_count": 1034
} | 87 |
# The Problem of Variance in Reinforce [[the-problem-of-variance-in-reinforce]]
In Reinforce, we want to **increase the probability of actions in a trajectory proportionally to how high the return is**.
<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit8/pg.jpg" ... | deep-rl-class/units/en/unit6/variance-problem.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit6/variance-problem.mdx",
"repo_id": "deep-rl-class",
"token_count": 711
} | 88 |
# Introduction [[introduction]]
<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit9/thumbnail.png" alt="Unit 8"/>
In Unit 6, we learned about Advantage Actor Critic (A2C), a hybrid architecture combining value-based and policy-based methods that helps to stabilize ... | deep-rl-class/units/en/unit8/introduction.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit8/introduction.mdx",
"repo_id": "deep-rl-class",
"token_count": 533
} | 89 |
# Introduction
<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit12/thumbnail.png" alt="Unit bonus 3 thumbnail"/>
Congratulations on finishing this course! **You now have a solid background in Deep Reinforcement Learning**.
But this course was just the beginning o... | deep-rl-class/units/en/unitbonus3/introduction.mdx/0 | {
"file_path": "deep-rl-class/units/en/unitbonus3/introduction.mdx",
"repo_id": "deep-rl-class",
"token_count": 171
} | 90 |
import argparse
import sys
sys.path.append(".")
from base_classes import LCMLoRATextToImageBenchmark # noqa: E402
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument(
"--ckpt",
type=str,
default="stabilityai/stable-diffusion-xl-base-1.0",
)
pars... | diffusers/benchmarks/benchmark_t2i_lcm_lora.py/0 | {
"file_path": "diffusers/benchmarks/benchmark_t2i_lcm_lora.py",
"repo_id": "diffusers",
"token_count": 273
} | 91 |
- sections:
- local: index
title: 🧨 Diffusers
- local: quicktour
title: Quicktour
- local: stable_diffusion
title: Effective and efficient diffusion
- local: installation
title: Installation
title: Get started
- sections:
- local: tutorials/tutorial_overview
title: Overview
- local: u... | diffusers/docs/source/en/_toctree.yml/0 | {
"file_path": "diffusers/docs/source/en/_toctree.yml",
"repo_id": "diffusers",
"token_count": 6273
} | 92 |
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | diffusers/docs/source/en/api/models/consistency_decoder_vae.md/0 | {
"file_path": "diffusers/docs/source/en/api/models/consistency_decoder_vae.md",
"repo_id": "diffusers",
"token_count": 383
} | 93 |
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to... | diffusers/docs/source/en/api/pipelines/kandinsky.md/0 | {
"file_path": "diffusers/docs/source/en/api/pipelines/kandinsky.md",
"repo_id": "diffusers",
"token_count": 850
} | 94 |
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | diffusers/docs/source/en/api/pipelines/stable_cascade.md/0 | {
"file_path": "diffusers/docs/source/en/api/pipelines/stable_cascade.md",
"repo_id": "diffusers",
"token_count": 2836
} | 95 |
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | diffusers/docs/source/en/optimization/deepcache.md/0 | {
"file_path": "diffusers/docs/source/en/optimization/deepcache.md",
"repo_id": "diffusers",
"token_count": 1912
} | 96 |
<!--Copyright 2024 Custom Diffusion authors 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... | diffusers/docs/source/en/training/custom_diffusion.md/0 | {
"file_path": "diffusers/docs/source/en/training/custom_diffusion.md",
"repo_id": "diffusers",
"token_count": 5470
} | 97 |
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | diffusers/docs/source/en/tutorials/basic_training.md/0 | {
"file_path": "diffusers/docs/source/en/tutorials/basic_training.md",
"repo_id": "diffusers",
"token_count": 6186
} | 98 |
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | diffusers/docs/source/en/using-diffusers/img2img.md/0 | {
"file_path": "diffusers/docs/source/en/using-diffusers/img2img.md",
"repo_id": "diffusers",
"token_count": 9649
} | 99 |
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | diffusers/docs/source/en/using-diffusers/reusing_seeds.md/0 | {
"file_path": "diffusers/docs/source/en/using-diffusers/reusing_seeds.md",
"repo_id": "diffusers",
"token_count": 1099
} | 100 |
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | diffusers/docs/source/ja/quicktour.md/0 | {
"file_path": "diffusers/docs/source/ja/quicktour.md",
"repo_id": "diffusers",
"token_count": 7835
} | 101 |
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | diffusers/docs/source/ko/optimization/tome.md/0 | {
"file_path": "diffusers/docs/source/ko/optimization/tome.md",
"repo_id": "diffusers",
"token_count": 4366
} | 102 |
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | diffusers/docs/source/ko/training/unconditional_training.md/0 | {
"file_path": "diffusers/docs/source/ko/training/unconditional_training.md",
"repo_id": "diffusers",
"token_count": 3095
} | 103 |
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | diffusers/docs/source/ko/using-diffusers/reproducibility.md/0 | {
"file_path": "diffusers/docs/source/ko/using-diffusers/reproducibility.md",
"repo_id": "diffusers",
"token_count": 6163
} | 104 |
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | diffusers/docs/source/zh/quicktour.md/0 | {
"file_path": "diffusers/docs/source/zh/quicktour.md",
"repo_id": "diffusers",
"token_count": 8423
} | 105 |
# 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... | diffusers/examples/community/ddim_noise_comparative_analysis.py/0 | {
"file_path": "diffusers/examples/community/ddim_noise_comparative_analysis.py",
"repo_id": "diffusers",
"token_count": 3417
} | 106 |
## ----------------------------------------------------------
# A SDXL pipeline can take unlimited weighted prompt
#
# Author: Andrew Zhu
# Github: https://github.com/xhinker
# Medium: https://medium.com/@xhinker
## -----------------------------------------------------------
import inspect
import os
from typing import... | diffusers/examples/community/lpw_stable_diffusion_xl.py/0 | {
"file_path": "diffusers/examples/community/lpw_stable_diffusion_xl.py",
"repo_id": "diffusers",
"token_count": 47271
} | 107 |
# Copyright 2024 TencentARC and 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... | diffusers/examples/community/pipeline_stable_diffusion_xl_controlnet_adapter.py/0 | {
"file_path": "diffusers/examples/community/pipeline_stable_diffusion_xl_controlnet_adapter.py",
"repo_id": "diffusers",
"token_count": 32940
} | 108 |
# Inspired by: https://github.com/haofanwang/ControlNet-for-Diffusers/
import inspect
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import numpy as np
import PIL.Image
import torch
import torch.nn.functional as F
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from di... | diffusers/examples/community/stable_diffusion_controlnet_inpaint.py/0 | {
"file_path": "diffusers/examples/community/stable_diffusion_controlnet_inpaint.py",
"repo_id": "diffusers",
"token_count": 23711
} | 109 |
import inspect
import os
import random
import re
from dataclasses import dataclass
from typing import Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers.configuration_utils import FrozenDict
from diffusers.models import Autoencod... | diffusers/examples/community/wildcard_stable_diffusion.py/0 | {
"file_path": "diffusers/examples/community/wildcard_stable_diffusion.py",
"repo_id": "diffusers",
"token_count": 9011
} | 110 |
# coding=utf-8
# Copyright 2024 HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ag... | diffusers/examples/controlnet/test_controlnet.py/0 | {
"file_path": "diffusers/examples/controlnet/test_controlnet.py",
"repo_id": "diffusers",
"token_count": 2010
} | 111 |
# coding=utf-8
# Copyright 2024 HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ag... | diffusers/examples/dreambooth/test_dreambooth_lora_edm.py/0 | {
"file_path": "diffusers/examples/dreambooth/test_dreambooth_lora_edm.py",
"repo_id": "diffusers",
"token_count": 1864
} | 112 |
#!/usr/bin/env python
# coding=utf-8
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | diffusers/examples/kandinsky2_2/text_to_image/train_text_to_image_decoder.py/0 | {
"file_path": "diffusers/examples/kandinsky2_2/text_to_image/train_text_to_image_decoder.py",
"repo_id": "diffusers",
"token_count": 16368
} | 113 |
## Diffusers examples with Intel optimizations
**This research project is not actively maintained by the diffusers team. For any questions or comments, please make sure to tag @hshen14 .**
This aims to provide diffusers examples with Intel optimizations such as Bfloat16 for training/fine-tuning acceleration and 8-bit... | diffusers/examples/research_projects/intel_opts/README.md/0 | {
"file_path": "diffusers/examples/research_projects/intel_opts/README.md",
"repo_id": "diffusers",
"token_count": 528
} | 114 |
#!/usr/bin/env python
# coding=utf-8
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | diffusers/examples/text_to_image/train_text_to_image_lora_sdxl.py/0 | {
"file_path": "diffusers/examples/text_to_image/train_text_to_image_lora_sdxl.py",
"repo_id": "diffusers",
"token_count": 24929
} | 115 |
#!/usr/bin/env python3
import argparse
import math
import os
from copy import deepcopy
import requests
import torch
from audio_diffusion.models import DiffusionAttnUnet1D
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNet1DModel
MODELS_MAP = {
... | diffusers/scripts/convert_dance_diffusion_to_diffusers.py/0 | {
"file_path": "diffusers/scripts/convert_dance_diffusion_to_diffusers.py",
"repo_id": "diffusers",
"token_count": 4637
} | 116 |
# coding=utf-8
# Copyright 2024 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... | diffusers/scripts/convert_ms_text_to_video_to_diffusers.py/0 | {
"file_path": "diffusers/scripts/convert_ms_text_to_video_to_diffusers.py",
"repo_id": "diffusers",
"token_count": 8414
} | 117 |
from diffusers.utils import is_accelerate_available, logging
if is_accelerate_available():
pass
logger = logging.get_logger(__name__) # pylint: disable=invalid-name
def create_unet_diffusers_config(original_config, image_size: int, controlnet=False):
"""
Creates a config for the diffusers based on the... | diffusers/scripts/convert_svd_to_diffusers.py/0 | {
"file_path": "diffusers/scripts/convert_svd_to_diffusers.py",
"repo_id": "diffusers",
"token_count": 14781
} | 118 |
# 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... | diffusers/src/diffusers/commands/env.py/0 | {
"file_path": "diffusers/src/diffusers/commands/env.py",
"repo_id": "diffusers",
"token_count": 1069
} | 119 |
# coding=utf-8
# Copyright 2024 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... | diffusers/src/diffusers/loaders/peft.py/0 | {
"file_path": "diffusers/src/diffusers/loaders/peft.py",
"repo_id": "diffusers",
"token_count": 3289
} | 120 |
# 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... | diffusers/src/diffusers/models/autoencoders/autoencoder_kl_temporal_decoder.py/0 | {
"file_path": "diffusers/src/diffusers/models/autoencoders/autoencoder_kl_temporal_decoder.py",
"repo_id": "diffusers",
"token_count": 7179
} | 121 |
# coding=utf-8
# Copyright 2024 HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ag... | diffusers/src/diffusers/models/normalization.py/0 | {
"file_path": "diffusers/src/diffusers/models/normalization.py",
"repo_id": "diffusers",
"token_count": 4029
} | 122 |
# 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... | diffusers/src/diffusers/models/unet_2d_blocks.py/0 | {
"file_path": "diffusers/src/diffusers/models/unet_2d_blocks.py",
"repo_id": "diffusers",
"token_count": 7248
} | 123 |
# 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... | diffusers/src/diffusers/models/unets/unet_stable_cascade.py/0 | {
"file_path": "diffusers/src/diffusers/models/unets/unet_stable_cascade.py",
"repo_id": "diffusers",
"token_count": 14544
} | 124 |
from typing import TYPE_CHECKING
from ...utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
_dummy_objects = {}
_import_structure = {}
try:
if not (is_transformers_available() and is... | diffusers/src/diffusers/pipelines/audioldm/__init__.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/audioldm/__init__.py",
"repo_id": "diffusers",
"token_count": 581
} | 125 |
# Copyright 2024 Salesforce.com, inc.
# 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/LICENS... | diffusers/src/diffusers/pipelines/controlnet/pipeline_controlnet_blip_diffusion.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/controlnet/pipeline_controlnet_blip_diffusion.py",
"repo_id": "diffusers",
"token_count": 7632
} | 126 |
# 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... | diffusers/src/diffusers/pipelines/deprecated/audio_diffusion/mel.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/deprecated/audio_diffusion/mel.py",
"repo_id": "diffusers",
"token_count": 2698
} | 127 |
from typing import TYPE_CHECKING
from ...utils import DIFFUSERS_SLOW_IMPORT, _LazyModule
_import_structure = {"pipeline_dit": ["DiTPipeline"]}
if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
from .pipeline_dit import DiTPipeline
else:
import sys
sys.modules[__name__] = _LazyModule(
__name__,
... | diffusers/src/diffusers/pipelines/dit/__init__.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/dit/__init__.py",
"repo_id": "diffusers",
"token_count": 177
} | 128 |
# 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... | diffusers/src/diffusers/pipelines/kandinsky2_2/pipeline_kandinsky2_2_controlnet_img2img.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/kandinsky2_2/pipeline_kandinsky2_2_controlnet_img2img.py",
"repo_id": "diffusers",
"token_count": 7538
} | 129 |
import inspect
import math
from itertools import repeat
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
import torch.nn.functional as F
from packaging import version
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from ...configuration_utils import FrozenDic... | diffusers/src/diffusers/pipelines/ledits_pp/pipeline_leditspp_stable_diffusion.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/ledits_pp/pipeline_leditspp_stable_diffusion.py",
"repo_id": "diffusers",
"token_count": 35679
} | 130 |
# 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... | diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_flax_stable_diffusion.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_flax_stable_diffusion.py",
"repo_id": "diffusers",
"token_count": 9012
} | 131 |
# 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... | diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_stable_unclip.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_stable_unclip.py",
"repo_id": "diffusers",
"token_count": 19693
} | 132 |
import numpy as np
import torch
from ...utils import is_invisible_watermark_available
if is_invisible_watermark_available():
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L... | diffusers/src/diffusers/pipelines/stable_diffusion_xl/watermark.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/stable_diffusion_xl/watermark.py",
"repo_id": "diffusers",
"token_count": 509
} | 133 |
from typing import TYPE_CHECKING
from ...utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
is_transformers_available,
)
_dummy_objects = {}
_import_structure = {}
try:
if not (is_transformers_available() and is_torch_available()):
... | diffusers/src/diffusers/pipelines/unidiffuser/__init__.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/unidiffuser/__init__.py",
"repo_id": "diffusers",
"token_count": 733
} | 134 |
# Copyright 2024 NVIDIA and 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 b... | diffusers/src/diffusers/schedulers/deprecated/scheduling_karras_ve.py/0 | {
"file_path": "diffusers/src/diffusers/schedulers/deprecated/scheduling_karras_ve.py",
"repo_id": "diffusers",
"token_count": 4089
} | 135 |
# Copyright 2024 Zhejiang University Team and 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
#
#... | diffusers/src/diffusers/schedulers/scheduling_pndm.py/0 | {
"file_path": "diffusers/src/diffusers/schedulers/scheduling_pndm.py",
"repo_id": "diffusers",
"token_count": 9459
} | 136 |
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def deprecate(*args, take_from: Optional[Union[Dict, Any]] = None, standard_warn=True, stacklevel=2):
from .. import __version__
deprecated_kwargs = take_from
values = ()
if not isinstance(args... | diffusers/src/diffusers/utils/deprecation_utils.py/0 | {
"file_path": "diffusers/src/diffusers/utils/deprecation_utils.py",
"repo_id": "diffusers",
"token_count": 793
} | 137 |
# coding=utf-8
# Copyright 2024 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... | diffusers/src/diffusers/utils/hub_utils.py/0 | {
"file_path": "diffusers/src/diffusers/utils/hub_utils.py",
"repo_id": "diffusers",
"token_count": 9131
} | 138 |
# coding=utf-8
# Copyright 2024 HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ag... | diffusers/tests/models/unets/test_models_unet_2d.py/0 | {
"file_path": "diffusers/tests/models/unets/test_models_unet_2d.py",
"repo_id": "diffusers",
"token_count": 5100
} | 139 |
import pickle as pkl
import unittest
from dataclasses import dataclass
from typing import List, Union
import numpy as np
import PIL.Image
from diffusers.utils.outputs import BaseOutput
from diffusers.utils.testing_utils import require_torch
@dataclass
class CustomOutput(BaseOutput):
images: Union[List[PIL.Image... | diffusers/tests/others/test_outputs.py/0 | {
"file_path": "diffusers/tests/others/test_outputs.py",
"repo_id": "diffusers",
"token_count": 1506
} | 140 |
# coding=utf-8
# Copyright 2024 HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ag... | diffusers/tests/pipelines/blipdiffusion/test_blipdiffusion.py/0 | {
"file_path": "diffusers/tests/pipelines/blipdiffusion/test_blipdiffusion.py",
"repo_id": "diffusers",
"token_count": 3065
} | 141 |
# coding=utf-8
# Copyright 2024 HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ag... | diffusers/tests/pipelines/kandinsky/test_kandinsky_combined.py/0 | {
"file_path": "diffusers/tests/pipelines/kandinsky/test_kandinsky_combined.py",
"repo_id": "diffusers",
"token_count": 5548
} | 142 |
# coding=utf-8
# Copyright 2024 HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ag... | diffusers/tests/pipelines/stable_diffusion/test_onnx_stable_diffusion_inpaint.py/0 | {
"file_path": "diffusers/tests/pipelines/stable_diffusion/test_onnx_stable_diffusion_inpaint.py",
"repo_id": "diffusers",
"token_count": 2242
} | 143 |
# coding=utf-8
# Copyright 2024 HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ag... | diffusers/tests/pipelines/stable_diffusion_2/test_stable_diffusion_v_pred.py/0 | {
"file_path": "diffusers/tests/pipelines/stable_diffusion_2/test_stable_diffusion_v_pred.py",
"repo_id": "diffusers",
"token_count": 10152
} | 144 |
# coding=utf-8
# Copyright 2024 HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ag... | diffusers/tests/pipelines/stable_diffusion_safe/test_safe_diffusion.py/0 | {
"file_path": "diffusers/tests/pipelines/stable_diffusion_safe/test_safe_diffusion.py",
"repo_id": "diffusers",
"token_count": 7442
} | 145 |
# coding=utf-8
# Copyright 2024 HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ag... | diffusers/tests/pipelines/test_pipelines.py/0 | {
"file_path": "diffusers/tests/pipelines/test_pipelines.py",
"repo_id": "diffusers",
"token_count": 38900
} | 146 |
import tempfile
import unittest
import torch
from diffusers import (
EDMDPMSolverMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class EDMDPMSolverMultistepSchedulerTest(SchedulerCommonTest):
scheduler_classes = (EDMDPMSolverMultistepScheduler,)
forward_default_kwargs = (("num_in... | diffusers/tests/schedulers/test_scheduler_edm_dpmsolver_multistep.py/0 | {
"file_path": "diffusers/tests/schedulers/test_scheduler_edm_dpmsolver_multistep.py",
"repo_id": "diffusers",
"token_count": 5436
} | 147 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class UniPCMultistepSchedulerTest(SchedulerCommonTest):
scheduler_classes = (UniPCM... | diffusers/tests/schedulers/test_scheduler_unipc.py/0 | {
"file_path": "diffusers/tests/schedulers/test_scheduler_unipc.py",
"repo_id": "diffusers",
"token_count": 6988
} | 148 |
#!/usr/bin/env python3
# coding=utf-8
# Copyright 2024 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
#
# Unles... | diffusers/utils/print_env.py/0 | {
"file_path": "diffusers/utils/print_env.py",
"repo_id": "diffusers",
"token_count": 424
} | 149 |
# Stable Diffusion Deep Dive
<CourseFloatingBanner unit={3}
classNames="absolute z-10 right-0 top-0"
notebooks={[
{label: "Stable Diffusion Deep Dive", value: "https://colab.research.google.com/github/huggingface/diffusion-models-class/blob/main/units/en/unit3/stable_diffusion_deep_dive.ipynb"},
{label: "S... | diffusion-models-class/units/en/unit3/3.mdx/0 | {
"file_path": "diffusion-models-class/units/en/unit3/3.mdx",
"repo_id": "diffusion-models-class",
"token_count": 20868
} | 150 |
# Sprint ControlNet en JAX/Diffusers
Bienvenue au sprint communautaire en JAX/Diffusers ! L'objectif de ce sprint est de travailler sur des modèles de diffusion amusants et créatifs en utilisant JAX et Diffusers.
Lors de cet événement, nous créerons diverses applications avec des modèles de diffusion en JAX/Flax et D... | diffusion-models-class/units/fr/events/4.mdx/0 | {
"file_path": "diffusion-models-class/units/fr/events/4.mdx",
"repo_id": "diffusion-models-class",
"token_count": 15277
} | 151 |
<jupyter_start><jupyter_text>Recherche sémantique avec FAISS (PyTorch) Installez les bibliothèques 🤗 Transformers et 🤗 Datasets pour exécuter ce *notebook*.<jupyter_code>!pip install datasets evaluate transformers[sentencepiece]
!pip install faiss-gpu
from huggingface_hub import hf_hub_url
data_files = hf_hub_url(
... | notebooks/course/fr/chapter5/section6_pt.ipynb/0 | {
"file_path": "notebooks/course/fr/chapter5/section6_pt.ipynb",
"repo_id": "notebooks",
"token_count": 1233
} | 152 |
<jupyter_start><jupyter_text>Finetuner un modèle de language masqué (TensorFlow) Installez les bibliothèques 🤗 *Datasets* et 🤗 *Transformers* pour exécuter ce *notebook*.<jupyter_code>!pip install datasets transformers[sentencepiece]
!apt install git-lfs<jupyter_output><empty_output><jupyter_text>Vous aurez besoin de... | notebooks/course/fr/chapter7/section3_tf.ipynb/0 | {
"file_path": "notebooks/course/fr/chapter7/section3_tf.ipynb",
"repo_id": "notebooks",
"token_count": 2949
} | 153 |
<jupyter_start><jupyter_text>Comprendre la classe Interface Installez les bibliothèques 🤗 Transformers et 🤗 Gradio pour exécuter ce *notebook*.<jupyter_code>!pip install datasets transformers[sentencepiece]
!pip install gradio
import numpy as np
import gradio as gr
def reverse_audio(audio):
sr, data = audio
... | notebooks/course/fr/chapter9/section3.ipynb/0 | {
"file_path": "notebooks/course/fr/chapter9/section3.ipynb",
"repo_id": "notebooks",
"token_count": 759
} | 154 |
<jupyter_start><jupyter_text>Image super-resolution using Latent Diffusion This colab notebook shows how to use the Latent Diffusion image super-resolution model using 🧨 [diffusers](https://github.com/huggingface/diffusers) libray.The model was originally released in [Latent Diffusion repo](https://github.com/CompVis/... | notebooks/diffusers/latent_diffusion_upscaler.ipynb/0 | {
"file_path": "notebooks/diffusers/latent_diffusion_upscaler.ipynb",
"repo_id": "notebooks",
"token_count": 656
} | 155 |
# adapted from https://github.com/huggingface/notebooks/blob/main/transformers_doc/en/pytorch/image_captioning.ipynb
# This example demonstrates normal finetuning (w/o peft) - for the sake of keeping the memory
# requirements small it freezes the original pre-trained text and image layers to keep the memory
# requirem... | notebooks/examples/idefics/finetune_image_captioning.py/0 | {
"file_path": "notebooks/examples/idefics/finetune_image_captioning.py",
"repo_id": "notebooks",
"token_count": 1670
} | 156 |
<jupyter_start><jupyter_text>If you're opening this Notebook on colab, you will probably need to install 🤗 Transformers as well as some other libraries. Uncomment the following cell and run it.<jupyter_code># Install
!pip install -q biopython transformers datasets huggingface_hub accelerate peft<jupyter_output>[2K ... | notebooks/examples/nucleotide_transformer_dna_sequence_modelling_with_peft.ipynb/0 | {
"file_path": "notebooks/examples/nucleotide_transformer_dna_sequence_modelling_with_peft.ipynb",
"repo_id": "notebooks",
"token_count": 8292
} | 157 |
<jupyter_start><jupyter_text>How to fine-tune a T5 model with ONNX RuntimeThis notebook is largely inspired by the summarization [notebook of Transformers](https://github.com/huggingface/notebooks/blob/main/examples/summarization.ipynb) which takes PyTorch as backend for fine tuning.Here you will use the `ORTSeq2SeqTra... | notebooks/examples/summarization_ort.ipynb/0 | {
"file_path": "notebooks/examples/summarization_ort.ipynb",
"repo_id": "notebooks",
"token_count": 6048
} | 158 |
<jupyter_start><jupyter_text>Getting started with Owl-ViTIn this notebook, we are going to run the [OWL-ViT](https://arxiv.org/abs/2205.06230) model (an open-vocabulary object detection model) by Google Research on scikit-image samples images. OWL-ViT: A Quick IntroOWL-ViT is an open-vocabulary object detector. Given ... | notebooks/examples/zeroshot_object_detection_with_owlvit.ipynb/0 | {
"file_path": "notebooks/examples/zeroshot_object_detection_with_owlvit.ipynb",
"repo_id": "notebooks",
"token_count": 4929
} | 159 |
import argparse
import logging
import os
import random
import sys
from datasets import load_from_disk
from sklearn.metrics import accuracy_score, precision_recall_fscore_support
import torch
from transformers import AutoModelForSequenceClassification, Trainer, TrainingArguments, AutoTokenizer
if __name__ == "__main_... | notebooks/sagemaker/06_sagemaker_metrics/scripts/train.py/0 | {
"file_path": "notebooks/sagemaker/06_sagemaker_metrics/scripts/train.py",
"repo_id": "notebooks",
"token_count": 1415
} | 160 |
# SageMaker push to hf.co/models example | notebooks/sagemaker/14_train_and_push_to_hub/README.md/0 | {
"file_path": "notebooks/sagemaker/14_train_and_push_to_hub/README.md",
"repo_id": "notebooks",
"token_count": 12
} | 161 |
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed... | peft/docs/source/developer_guides/model_merging.md/0 | {
"file_path": "peft/docs/source/developer_guides/model_merging.md",
"repo_id": "peft",
"token_count": 2263
} | 162 |
import gc
import os
import sys
import threading
import psutil
import torch
from accelerate import Accelerator
from datasets import load_dataset
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import (
AutoModelForCausalLM,
AutoTokenizer,
default_data_collator,
get_linear... | peft/examples/causal_language_modeling/peft_lora_clm_accelerate_ds_zero3_offload.py/0 | {
"file_path": "peft/examples/causal_language_modeling/peft_lora_clm_accelerate_ds_zero3_offload.py",
"repo_id": "peft",
"token_count": 6919
} | 163 |
# Copyright 2023-present the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or... | peft/examples/loftq_finetuning/train_gsm8k_llama.py/0 | {
"file_path": "peft/examples/loftq_finetuning/train_gsm8k_llama.py",
"repo_id": "peft",
"token_count": 14574
} | 164 |
<jupyter_start><jupyter_text>IntroductionIn this notebook, we will learn how to use [LoRA](https://arxiv.org/abs/2106.09685) from 🤗 PEFT to fine-tune a SegFormer model variant for semantic segmentation by ONLY using **14%** of the original trainable parameters of the model. LoRA adds low-rank "update matrices" to cert... | peft/examples/semantic_segmentation/semantic_segmentation_peft_lora.ipynb/0 | {
"file_path": "peft/examples/semantic_segmentation/semantic_segmentation_peft_lora.ipynb",
"repo_id": "peft",
"token_count": 8322
} | 165 |
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