text stringlengths 7 318k | id stringlengths 14 166 | metadata dict | __index_level_0__ int64 0 439 |
|---|---|---|---|
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.download_config import DownloadConfig
from ..download.streamin... | datasets/src/datasets/features/image.py/0 | {
"file_path": "datasets/src/datasets/features/image.py",
"repo_id": "datasets",
"token_count": 6802
} | 70 |
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.csv.csv import Csv
from ..utils import tqdm as hf_tqdm
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc i... | datasets/src/datasets/io/csv.py/0 | {
"file_path": "datasets/src/datasets/io/csv.py",
"repo_id": "datasets",
"token_count": 2536
} | 71 |
from typing import List
import datasets
from datasets.tasks import AudioClassification
from ..folder_based_builder import folder_based_builder
logger = datasets.utils.logging.get_logger(__name__)
class AudioFolderConfig(folder_based_builder.FolderBasedBuilderConfig):
"""Builder Config for AudioFolder."""
... | datasets/src/datasets/packaged_modules/audiofolder/audiofolder.py/0 | {
"file_path": "datasets/src/datasets/packaged_modules/audiofolder/audiofolder.py",
"repo_id": "datasets",
"token_count": 618
} | 72 |
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
logger = datasets.utils.logging.get_logger(__name__)
@dataclass
class ParquetConfig(datasets.BuilderConfig):
"""BuilderCo... | datasets/src/datasets/packaged_modules/parquet/parquet.py/0 | {
"file_path": "datasets/src/datasets/packaged_modules/parquet/parquet.py",
"repo_id": "datasets",
"token_count": 2068
} | 73 |
from typing import Optional
from ..utils.logging import get_logger
from .audio_classification import AudioClassification
from .automatic_speech_recognition import AutomaticSpeechRecognition
from .base import TaskTemplate
from .image_classification import ImageClassification
from .language_modeling import LanguageModel... | datasets/src/datasets/tasks/__init__.py/0 | {
"file_path": "datasets/src/datasets/tasks/__init__.py",
"repo_id": "datasets",
"token_count": 506
} | 74 |
# deprecated, please use datasets.download.download_manager
| datasets/src/datasets/utils/download_manager.py/0 | {
"file_path": "datasets/src/datasets/utils/download_manager.py",
"repo_id": "datasets",
"token_count": 13
} | 75 |
name: "" # Filename comes here
allow_empty: false
allow_empty_text: true
subsections:
- name: "Dataset Card for X" # First-level markdown heading
allow_empty: false
allow_empty_text: true
subsections:
- name: "Table of Contents"
allow_empty: false
allow_empty_text: false
subs... | datasets/src/datasets/utils/resources/readme_structure.yaml/0 | {
"file_path": "datasets/src/datasets/utils/resources/readme_structure.yaml",
"repo_id": "datasets",
"token_count": 1924
} | 76 |
import os
import tarfile
import warnings
import numpy as np
import pandas as pd
import pyarrow as pa
import pytest
from datasets import Dataset, Features, Image, Sequence, Value, concatenate_datasets, load_dataset
from datasets.features.image import encode_np_array, image_to_bytes
from ..utils import require_pil
@... | datasets/tests/features/test_image.py/0 | {
"file_path": "datasets/tests/features/test_image.py",
"repo_id": "datasets",
"token_count": 11376
} | 77 |
from pathlib import Path
import pytest
from datasets import load_dataset
from datasets.packaged_modules.cache.cache import Cache
SAMPLE_DATASET_TWO_CONFIG_IN_METADATA = "hf-internal-testing/audiofolder_two_configs_in_metadata"
def test_cache(text_dir: Path):
ds = load_dataset(str(text_dir))
hash = Path(ds... | datasets/tests/packaged_modules/test_cache.py/0 | {
"file_path": "datasets/tests/packaged_modules/test_cache.py",
"repo_id": "datasets",
"token_count": 960
} | 78 |
import os
import sys
from pathlib import Path
import pytest
from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node
from .utils import execute_subprocess_async, get_torch_dist_unique_port, require_torch
def test_split_dataset_by_node_map_style():
full_ds = Dataset.f... | datasets/tests/test_distributed.py/0 | {
"file_path": "datasets/tests/test_distributed.py",
"repo_id": "datasets",
"token_count": 1926
} | 79 |
import re
import sys
import tempfile
import unittest
from pathlib import Path
import pytest
import yaml
from huggingface_hub import DatasetCard, DatasetCardData
from datasets.config import METADATA_CONFIGS_FIELD
from datasets.info import DatasetInfo
from datasets.utils.metadata import MetadataConfigs
def _dedent(st... | datasets/tests/test_metadata_util.py/0 | {
"file_path": "datasets/tests/test_metadata_util.py",
"repo_id": "datasets",
"token_count": 5452
} | 80 |
import pytest
from datasets.utils.version import Version
@pytest.mark.parametrize(
"other, expected_equality",
[
(Version("1.0.0"), True),
("1.0.0", True),
(Version("2.0.0"), False),
("2.0.0", False),
("1", False),
("a", False),
(1, False),
(Non... | datasets/tests/test_version.py/0 | {
"file_path": "datasets/tests/test_version.py",
"repo_id": "datasets",
"token_count": 254
} | 81 |
<jupyter_start><jupyter_text>Unit 5: An Introduction to ML-Agents In this notebook, you'll learn about ML-Agents and train two agents.- The first one will learn to **shoot snowballs onto spawning targets**.- The second need to press a button to spawn a pyramid, then navigate to the pyramid, knock it over, **and move to... | deep-rl-class/notebooks/unit5/unit5.ipynb/0 | {
"file_path": "deep-rl-class/notebooks/unit5/unit5.ipynb",
"repo_id": "deep-rl-class",
"token_count": 4123
} | 82 |
# Glossary [[glossary]]
This is a community-created glossary. Contributions are welcomed!
### Agent
An agent learns to **make decisions by trial and error, with rewards and punishments from the surroundings**.
### Environment
An environment is a simulated world **where an agent can learn by interacting with it**.
... | deep-rl-class/units/en/unit1/glossary.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit1/glossary.mdx",
"repo_id": "deep-rl-class",
"token_count": 775
} | 83 |
# Mid-way Quiz [[mid-way-quiz]]
The best way to learn and [to avoid the illusion of competence](https://www.coursera.org/lecture/learning-how-to-learn/illusions-of-competence-BuFzf) **is to test yourself.** This will help you to find **where you need to reinforce your knowledge**.
### Q1: What are the two main appro... | deep-rl-class/units/en/unit2/mid-way-quiz.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit2/mid-way-quiz.mdx",
"repo_id": "deep-rl-class",
"token_count": 1100
} | 84 |
# Quiz [[quiz]]
The best way to learn and [to avoid the illusion of competence](https://www.coursera.org/lecture/learning-how-to-learn/illusions-of-competence-BuFzf) **is to test yourself.** This will help you to find **where you need to reinforce your knowledge**.
### Q1: We mentioned Q Learning is a tabular method.... | deep-rl-class/units/en/unit3/quiz.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit3/quiz.mdx",
"repo_id": "deep-rl-class",
"token_count": 1099
} | 85 |
# An Introduction to Unity ML-Agents [[introduction-to-ml-agents]]
<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit7/thumbnail.png" alt="thumbnail"/>
One of the challenges in Reinforcement Learning is **creating environments**. Fortunately for us, we can use game... | deep-rl-class/units/en/unit5/introduction.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit5/introduction.mdx",
"repo_id": "deep-rl-class",
"token_count": 696
} | 86 |
# Designing Multi-Agents systems
For this section, you're going to watch this excellent introduction to multi-agents made by <a href="https://www.youtube.com/channel/UCq0imsn84ShAe9PBOFnoIrg"> Brian Douglas </a>.
<Youtube id="qgb0gyrpiGk" />
In this video, Brian talked about how to design multi-agent systems. He sp... | deep-rl-class/units/en/unit7/multi-agent-setting.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit7/multi-agent-setting.mdx",
"repo_id": "deep-rl-class",
"token_count": 847
} | 87 |
# Play with Huggy [[play]]
Now that you've trained Huggy and pushed it to the Hub. **You will be able to play with him ❤️**
For this step it’s simple:
- Open the Huggy game in your browser: https://huggingface.co/spaces/ThomasSimonini/Huggy
- Click on Play with my Huggy model
<img src="https://huggingface.co/datase... | deep-rl-class/units/en/unitbonus1/play.mdx/0 | {
"file_path": "deep-rl-class/units/en/unitbonus1/play.mdx",
"repo_id": "deep-rl-class",
"token_count": 271
} | 88 |
import argparse
import sys
sys.path.append(".")
from base_classes import ControlNetBenchmark, ControlNetSDXLBenchmark # noqa: E402
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument(
"--ckpt",
type=str,
default="lllyasviel/sd-controlnet-canny",
... | diffusers/benchmarks/benchmark_controlnet.py/0 | {
"file_path": "diffusers/benchmarks/benchmark_controlnet.py",
"repo_id": "diffusers",
"token_count": 352
} | 89 |
<!--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 applicable law or agreed... | diffusers/docs/source/en/api/logging.md/0 | {
"file_path": "diffusers/docs/source/en/api/logging.md",
"repo_id": "diffusers",
"token_count": 1352
} | 90 |
<!--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 applicable law or agreed... | diffusers/docs/source/en/api/pipelines/deepfloyd_if.md/0 | {
"file_path": "diffusers/docs/source/en/api/pipelines/deepfloyd_if.md",
"repo_id": "diffusers",
"token_count": 6744
} | 91 |
<!--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 applicable law or agreed... | diffusers/docs/source/en/api/pipelines/stable_diffusion/stable_diffusion_xl.md/0 | {
"file_path": "diffusers/docs/source/en/api/pipelines/stable_diffusion/stable_diffusion_xl.md",
"repo_id": "diffusers",
"token_count": 1006
} | 92 |
<!--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 applicable law or agreed... | diffusers/docs/source/en/optimization/habana.md/0 | {
"file_path": "diffusers/docs/source/en/optimization/habana.md",
"repo_id": "diffusers",
"token_count": 1400
} | 93 |
<!--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 applicable law or agreed... | diffusers/docs/source/en/training/distributed_inference.md/0 | {
"file_path": "diffusers/docs/source/en/training/distributed_inference.md",
"repo_id": "diffusers",
"token_count": 1500
} | 94 |
<!--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 applicable law or agreed... | diffusers/docs/source/en/tutorials/tutorial_overview.md/0 | {
"file_path": "diffusers/docs/source/en/tutorials/tutorial_overview.md",
"repo_id": "diffusers",
"token_count": 413
} | 95 |
<!--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 applicable law or agreed... | diffusers/docs/source/en/using-diffusers/inference_with_lcm_lora.md/0 | {
"file_path": "diffusers/docs/source/en/using-diffusers/inference_with_lcm_lora.md",
"repo_id": "diffusers",
"token_count": 5694
} | 96 |
<!--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 applicable law or agreed... | diffusers/docs/source/en/using-diffusers/stable_diffusion_jax_how_to.md/0 | {
"file_path": "diffusers/docs/source/en/using-diffusers/stable_diffusion_jax_how_to.md",
"repo_id": "diffusers",
"token_count": 3028
} | 97 |
<!--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 applicable law or agreed... | diffusers/docs/source/ko/training/controlnet.md/0 | {
"file_path": "diffusers/docs/source/ko/training/controlnet.md",
"repo_id": "diffusers",
"token_count": 7783
} | 98 |
<!--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 applicable law or agreed... | diffusers/docs/source/ko/using-diffusers/controlling_generation.md/0 | {
"file_path": "diffusers/docs/source/ko/using-diffusers/controlling_generation.md",
"repo_id": "diffusers",
"token_count": 14042
} | 99 |
# 세이프텐서 로드
[safetensors](https://github.com/huggingface/safetensors)는 텐서를 저장하고 로드하기 위한 안전하고 빠른 파일 형식입니다. 일반적으로 PyTorch 모델 가중치는 Python의 [`pickle`](https://docs.python.org/3/library/pickle.html) 유틸리티를 사용하여 `.bin` 파일에 저장되거나 `피클`됩니다. 그러나 `피클`은 안전하지 않으며 피클된 파일에는 실행될 수 있는 악성 코드가 포함될 수 있습니다. 세이프텐서는 `피클`의 안전한 대안으로 모델 가중치를 공유하... | diffusers/docs/source/ko/using-diffusers/using_safetensors.md/0 | {
"file_path": "diffusers/docs/source/ko/using-diffusers/using_safetensors.md",
"repo_id": "diffusers",
"token_count": 4065
} | 100 |
# 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... | diffusers/examples/amused/train_amused.py/0 | {
"file_path": "diffusers/examples/amused/train_amused.py",
"repo_id": "diffusers",
"token_count": 17460
} | 101 |
import inspect
import time
from pathlib import Path
from typing import Callable, List, Optional, Union
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import DiffusionPipeline
from diffusers.configuration_utils import FrozenDict
from diffusers.m... | diffusers/examples/community/interpolate_stable_diffusion.py/0 | {
"file_path": "diffusers/examples/community/interpolate_stable_diffusion.py",
"repo_id": "diffusers",
"token_count": 11720
} | 102 |
# 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... | diffusers/examples/community/pipeline_animatediff_controlnet.py/0 | {
"file_path": "diffusers/examples/community/pipeline_animatediff_controlnet.py",
"repo_id": "diffusers",
"token_count": 24523
} | 103 |
# Copyright 2023 UC Berkeley 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
#
# Unless ... | diffusers/examples/community/scheduling_ufogen.py/0 | {
"file_path": "diffusers/examples/community/scheduling_ufogen.py",
"repo_id": "diffusers",
"token_count": 10909
} | 104 |
# DreamBooth training example
[DreamBooth](https://arxiv.org/abs/2208.12242) is a method to personalize text2image models like stable diffusion given just a few(3~5) images of a subject.
The `train_dreambooth.py` script shows how to implement the training procedure and adapt it for stable diffusion.
## Running local... | diffusers/examples/dreambooth/README.md/0 | {
"file_path": "diffusers/examples/dreambooth/README.md",
"repo_id": "diffusers",
"token_count": 9921
} | 105 |
import argparse
import math
import os
from pathlib import Path
import colossalai
import torch
import torch.nn.functional as F
import torch.utils.checkpoint
from colossalai.context.parallel_mode import ParallelMode
from colossalai.core import global_context as gpc
from colossalai.logging import disable_existing_loggers... | diffusers/examples/research_projects/colossalai/train_dreambooth_colossalai.py/0 | {
"file_path": "diffusers/examples/research_projects/colossalai/train_dreambooth_colossalai.py",
"repo_id": "diffusers",
"token_count": 11176
} | 106 |
# Dreambooth for the inpainting model
This script was added by @thedarkzeno .
Please note that this script is not actively maintained, you can open an issue and tag @thedarkzeno or @patil-suraj though.
```bash
export MODEL_NAME="runwayml/stable-diffusion-inpainting"
export INSTANCE_DIR="path-to-instance-images"
expo... | diffusers/examples/research_projects/dreambooth_inpaint/README.md/0 | {
"file_path": "diffusers/examples/research_projects/dreambooth_inpaint/README.md",
"repo_id": "diffusers",
"token_count": 1502
} | 107 |
# Show best practices for SDXL JAX
import time
import jax
import jax.numpy as jnp
import numpy as np
from flax.jax_utils import replicate
# Let's cache the model compilation, so that it doesn't take as long the next time around.
from jax.experimental.compilation_cache import compilation_cache as cc
from diffusers im... | diffusers/examples/research_projects/sdxl_flax/sdxl_single.py/0 | {
"file_path": "diffusers/examples/research_projects/sdxl_flax/sdxl_single.py",
"repo_id": "diffusers",
"token_count": 1341
} | 108 |
import argparse
import logging
import math
import os
import random
from pathlib import Path
import jax
import jax.numpy as jnp
import numpy as np
import optax
import torch
import torch.utils.checkpoint
import transformers
from datasets import load_dataset
from flax import jax_utils
from flax.training import train_stat... | diffusers/examples/text_to_image/train_text_to_image_flax.py/0 | {
"file_path": "diffusers/examples/text_to_image/train_text_to_image_flax.py",
"repo_id": "diffusers",
"token_count": 9737
} | 109 |
import argparse
import inspect
import logging
import math
import os
import shutil
from datetime import timedelta
from pathlib import Path
import accelerate
import datasets
import torch
import torch.nn.functional as F
from accelerate import Accelerator, InitProcessGroupKwargs
from accelerate.logging import get_logger
f... | diffusers/examples/unconditional_image_generation/train_unconditional.py/0 | {
"file_path": "diffusers/examples/unconditional_image_generation/train_unconditional.py",
"repo_id": "diffusers",
"token_count": 13301
} | 110 |
import math
import os
import urllib
import warnings
from argparse import ArgumentParser
import torch
import torch.nn as nn
import torch.nn.functional as F
from huggingface_hub.utils import insecure_hashlib
from safetensors.torch import load_file as stl
from tqdm import tqdm
from diffusers import AutoencoderKL, Consis... | diffusers/scripts/convert_consistency_decoder.py/0 | {
"file_path": "diffusers/scripts/convert_consistency_decoder.py",
"repo_id": "diffusers",
"token_count": 21911
} | 111 |
# coding=utf-8
# Copyright 2023, Haofan Wang, Qixun Wang, 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 re... | diffusers/scripts/convert_lora_safetensor_to_diffusers.py/0 | {
"file_path": "diffusers/scripts/convert_lora_safetensor_to_diffusers.py",
"repo_id": "diffusers",
"token_count": 2130
} | 112 |
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
} | 113 |
# 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... | diffusers/src/diffusers/commands/fp16_safetensors.py/0 | {
"file_path": "diffusers/src/diffusers/commands/fp16_safetensors.py",
"repo_id": "diffusers",
"token_count": 2249
} | 114 |
# 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... | diffusers/src/diffusers/loaders/single_file.py/0 | {
"file_path": "diffusers/src/diffusers/loaders/single_file.py",
"repo_id": "diffusers",
"token_count": 4965
} | 115 |
# Copyright 2023 Ollin Boer Bohan 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 ... | diffusers/src/diffusers/models/autoencoders/autoencoder_tiny.py/0 | {
"file_path": "diffusers/src/diffusers/models/autoencoders/autoencoder_tiny.py",
"repo_id": "diffusers",
"token_count": 6550
} | 116 |
from ..utils import deprecate
from .transformers.prior_transformer import PriorTransformer, PriorTransformerOutput
class PriorTransformerOutput(PriorTransformerOutput):
deprecation_message = "Importing `PriorTransformerOutput` from `diffusers.models.prior_transformer` is deprecated and this will be removed in a f... | diffusers/src/diffusers/models/prior_transformer.py/0 | {
"file_path": "diffusers/src/diffusers/models/prior_transformer.py",
"repo_id": "diffusers",
"token_count": 235
} | 117 |
# 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... | diffusers/src/diffusers/models/upsampling.py/0 | {
"file_path": "diffusers/src/diffusers/models/upsampling.py",
"repo_id": "diffusers",
"token_count": 7819
} | 118 |
from typing import TYPE_CHECKING
from ...utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
get_objects_from_module,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
_dummy_objects = {}
_import_structure = {}
try:
if not (is_tr... | diffusers/src/diffusers/pipelines/audioldm2/__init__.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/audioldm2/__init__.py",
"repo_id": "diffusers",
"token_count": 637
} | 119 |
# 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... | diffusers/src/diffusers/pipelines/controlnet/pipeline_controlnet_inpaint.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/controlnet/pipeline_controlnet_inpaint.py",
"repo_id": "diffusers",
"token_count": 35664
} | 120 |
from typing import TYPE_CHECKING
from ....utils import DIFFUSERS_SLOW_IMPORT, _LazyModule
_import_structure = {"pipeline_latent_diffusion_uncond": ["LDMPipeline"]}
if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
from .pipeline_latent_diffusion_uncond import LDMPipeline
else:
import sys
sys.modules[__name__]... | diffusers/src/diffusers/pipelines/deprecated/latent_diffusion_uncond/__init__.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/deprecated/latent_diffusion_uncond/__init__.py",
"repo_id": "diffusers",
"token_count": 190
} | 121 |
# 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... | diffusers/src/diffusers/pipelines/deprecated/stable_diffusion_variants/pipeline_stable_diffusion_inpaint_legacy.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/deprecated/stable_diffusion_variants/pipeline_stable_diffusion_inpaint_legacy.py",
"repo_id": "diffusers",
"token_count": 18283
} | 122 |
from typing import TYPE_CHECKING
from ...utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
get_objects_from_module,
is_torch_available,
is_transformers_available,
)
_dummy_objects = {}
_import_structure = {}
try:
if not (is_transformers_available() and is... | diffusers/src/diffusers/pipelines/i2vgen_xl/__init__.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/i2vgen_xl/__init__.py",
"repo_id": "diffusers",
"token_count": 532
} | 123 |
from typing import Callable, Dict, List, Optional, Union
import PIL.Image
import torch
from transformers import CLIPImageProcessor, CLIPTextModelWithProjection, CLIPTokenizer, CLIPVisionModelWithProjection
from ...models import PriorTransformer
from ...schedulers import UnCLIPScheduler
from ...utils import (
logg... | diffusers/src/diffusers/pipelines/kandinsky2_2/pipeline_kandinsky2_2_prior.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/kandinsky2_2/pipeline_kandinsky2_2_prior.py",
"repo_id": "diffusers",
"token_count": 11437
} | 124 |
# 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... | diffusers/src/diffusers/pipelines/paint_by_example/image_encoder.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/paint_by_example/image_encoder.py",
"repo_id": "diffusers",
"token_count": 943
} | 125 |
# Stable Diffusion
## Overview
Stable Diffusion was proposed in [Stable Diffusion Announcement](https://stability.ai/blog/stable-diffusion-announcement) by Patrick Esser and Robin Rombach and the Stability AI team.
The summary of the model is the following:
*Stable Diffusion is a text-to-image model that will empow... | diffusers/src/diffusers/pipelines/stable_diffusion/README.md/0 | {
"file_path": "diffusers/src/diffusers/pipelines/stable_diffusion/README.md",
"repo_id": "diffusers",
"token_count": 2465
} | 126 |
# 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... | diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_inpaint.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_inpaint.py",
"repo_id": "diffusers",
"token_count": 32442
} | 127 |
from typing import TYPE_CHECKING
from ...utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
get_objects_from_module,
is_k_diffusion_available,
is_k_diffusion_version,
is_torch_available,
is_transformers_available,
)
_dummy_objects = {}
_import_structure... | diffusers/src/diffusers/pipelines/stable_diffusion_k_diffusion/__init__.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/stable_diffusion_k_diffusion/__init__.py",
"repo_id": "diffusers",
"token_count": 812
} | 128 |
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/unclip/__init__.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/unclip/__init__.py",
"repo_id": "diffusers",
"token_count": 700
} | 129 |
# Copyright (c) 2022 Pablo Pernías MIT License
# Copyright 2023 UC Berkeley 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://... | diffusers/src/diffusers/schedulers/scheduling_ddpm_wuerstchen.py/0 | {
"file_path": "diffusers/src/diffusers/schedulers/scheduling_ddpm_wuerstchen.py",
"repo_id": "diffusers",
"token_count": 3662
} | 130 |
# Copyright 2023 Katherine Crowson 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... | diffusers/src/diffusers/schedulers/scheduling_lms_discrete.py/0 | {
"file_path": "diffusers/src/diffusers/schedulers/scheduling_lms_discrete.py",
"repo_id": "diffusers",
"token_count": 8761
} | 131 |
# 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 required by appl... | diffusers/src/diffusers/utils/constants.py/0 | {
"file_path": "diffusers/src/diffusers/utils/constants.py",
"repo_id": "diffusers",
"token_count": 820
} | 132 |
import io
import random
import struct
import tempfile
from contextlib import contextmanager
from typing import List, Union
import numpy as np
import PIL.Image
import PIL.ImageOps
from .import_utils import (
BACKENDS_MAPPING,
is_opencv_available,
)
from .logging import get_logger
global_rng = random.Random()... | diffusers/src/diffusers/utils/export_utils.py/0 | {
"file_path": "diffusers/src/diffusers/utils/export_utils.py",
"repo_id": "diffusers",
"token_count": 2016
} | 133 |
# coding=utf-8
# Copyright 2023 HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ag... | diffusers/tests/others/test_image_processor.py/0 | {
"file_path": "diffusers/tests/others/test_image_processor.py",
"repo_id": "diffusers",
"token_count": 5495
} | 134 |
# coding=utf-8
# Copyright 2023 HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ag... | diffusers/tests/pipelines/ddim/test_ddim.py/0 | {
"file_path": "diffusers/tests/pipelines/ddim/test_ddim.py",
"repo_id": "diffusers",
"token_count": 2231
} | 135 |
# coding=utf-8
# Copyright 2023 HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ag... | diffusers/tests/pipelines/kandinsky/test_kandinsky.py/0 | {
"file_path": "diffusers/tests/pipelines/kandinsky/test_kandinsky.py",
"repo_id": "diffusers",
"token_count": 4829
} | 136 |
# coding=utf-8
# Copyright 2023 HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ag... | diffusers/tests/pipelines/kandinsky3/test_kandinsky3_img2img.py/0 | {
"file_path": "diffusers/tests/pipelines/kandinsky3/test_kandinsky3_img2img.py",
"repo_id": "diffusers",
"token_count": 3406
} | 137 |
# coding=utf-8
# Copyright 2023 HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ag... | diffusers/tests/pipelines/stable_diffusion_gligen_text_image/test_stable_diffusion_gligen_text_image.py/0 | {
"file_path": "diffusers/tests/pipelines/stable_diffusion_gligen_text_image/test_stable_diffusion_gligen_text_image.py",
"repo_id": "diffusers",
"token_count": 3233
} | 138 |
# coding=utf-8
# Copyright 2023 HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ag... | diffusers/tests/pipelines/stable_diffusion_xl/test_stable_diffusion_xl_img2img.py/0 | {
"file_path": "diffusers/tests/pipelines/stable_diffusion_xl/test_stable_diffusion_xl_img2img.py",
"repo_id": "diffusers",
"token_count": 14478
} | 139 |
import torch
from diffusers import DDIMScheduler
from .test_schedulers import SchedulerCommonTest
class DDIMSchedulerTest(SchedulerCommonTest):
scheduler_classes = (DDIMScheduler,)
forward_default_kwargs = (("eta", 0.0), ("num_inference_steps", 50))
def get_scheduler_config(self, **kwargs):
con... | diffusers/tests/schedulers/test_scheduler_ddim.py/0 | {
"file_path": "diffusers/tests/schedulers/test_scheduler_ddim.py",
"repo_id": "diffusers",
"token_count": 3127
} | 140 |
import torch
from diffusers import KDPM2DiscreteScheduler
from diffusers.utils.testing_utils import torch_device
from .test_schedulers import SchedulerCommonTest
class KDPM2DiscreteSchedulerTest(SchedulerCommonTest):
scheduler_classes = (KDPM2DiscreteScheduler,)
num_inference_steps = 10
def get_schedul... | diffusers/tests/schedulers/test_scheduler_kdpm2_discrete.py/0 | {
"file_path": "diffusers/tests/schedulers/test_scheduler_kdpm2_discrete.py",
"repo_id": "diffusers",
"token_count": 2792
} | 141 |
# 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... | diffusers/utils/check_table.py/0 | {
"file_path": "diffusers/utils/check_table.py",
"repo_id": "diffusers",
"token_count": 3011
} | 142 |
<jupyter_start><jupyter_text>IntroductionThis notebook is going to cover the basics of how to use Stable Diffusion to create and modify images using existing pipelines. We'll also take a brief look at the key components within the pipeline, while leaving further exploration of them to the deep dive notebook. Specifical... | diffusion-models-class/unit3/01_stable_diffusion_introduction.ipynb/0 | {
"file_path": "diffusion-models-class/unit3/01_stable_diffusion_introduction.ipynb",
"repo_id": "diffusion-models-class",
"token_count": 6210
} | 143 |
# Introduction
<CourseFloatingBanner
unit={0}
classNames="absolute z-10 right-0 top-0"
/>
## Welcome to the course on diffusion models 🤗 !
## What to expect?
In this free course, you will:
- 👩🎓 Study the theory behind diffusion models
- 🧨 Learn how to generate images and audio with the popular 🤗 Diffu... | diffusion-models-class/units/en/unit0/1.mdx/0 | {
"file_path": "diffusion-models-class/units/en/unit0/1.mdx",
"repo_id": "diffusion-models-class",
"token_count": 1359
} | 144 |
# Sprint Dreambooth en Keras
Cette paget résume toutes les informations pertinentes requises pour l'événement. 📋.
## Introduction
Dreambooth est une technique de *finetuning* permettant d'enseigner de nouveaux concepts visuels à des modèles de diffusion conditionnés par le texte en utilisant seulement 3 à 5 images.... | diffusion-models-class/units/fr/events/3.mdx/0 | {
"file_path": "diffusion-models-class/units/fr/events/3.mdx",
"repo_id": "diffusion-models-class",
"token_count": 4273
} | 145 |
<jupyter_start><jupyter_text>Traduction (PyTorch) Installez les bibliothèques 🤗 *Datasets* et 🤗 *Transformers* pour exécuter ce *notebook*.<jupyter_code>!pip install datasets transformers[sentencepiece]
!pip install accelerate
# Pour exécuter l'entraînement sur TPU, vous devez décommenter la ligne suivante :
# !pip i... | notebooks/course/fr/chapter7/section4_pt.ipynb/0 | {
"file_path": "notebooks/course/fr/chapter7/section4_pt.ipynb",
"repo_id": "notebooks",
"token_count": 3791
} | 146 |
<jupyter_start><jupyter_text>Partager ses démos avec d'autres Installez les bibliothèques 🤗 Transformers et 🤗 Gradio pour exécuter ce *notebook*.<jupyter_code>!pip install datasets transformers[sentencepiece]
!pip install gradio
import gradio as gr
title = "Poser une question (en anglais) à Rick"
description = """
L... | notebooks/course/fr/chapter9/section4.ipynb/0 | {
"file_path": "notebooks/course/fr/chapter9/section4.ipynb",
"repo_id": "notebooks",
"token_count": 1441
} | 147 |
<jupyter_start><jupyter_text>IntroductionThis notebook is designed to run inference on the [Diffuser](https://arxiv.org/abs/2205.09991) planning model for model-based RL. The notebook is modified from the authors' [original](https://colab.research.google.com/drive/1YajKhu-CUIGBJeQPehjVPJcK_b38a8Nc?usp=sharingscrollTo=5... | notebooks/diffusers/reinforcement_learning_with_diffusers.ipynb/0 | {
"file_path": "notebooks/diffusers/reinforcement_learning_with_diffusers.ipynb",
"repo_id": "notebooks",
"token_count": 8060
} | 148 |
<jupyter_start><jupyter_text>IDEFICS: A Flamingo-based model, trained at scale for the community Finetuning Demo Notebook: Credit: [Flamingo blog](https://www.deepmind.com/blog/tackling-multiple-tasks-with-a-single-visual-language-model)This google colab notebook shows how to run predictions with the 4-bit quantized... | notebooks/examples/idefics/finetune_image_captioning_peft.ipynb/0 | {
"file_path": "notebooks/examples/idefics/finetune_image_captioning_peft.ipynb",
"repo_id": "notebooks",
"token_count": 3875
} | 149 |
<jupyter_start><jupyter_text>How to export 🤗 Transformers Models to ONNX ? [ONNX](http://onnx.ai/) is open format for machine learning models. It allows to save your neural network's computation graph in a framework agnostic way, which might be particulary helpful when deploying deep learning models.Indeed, businesses... | notebooks/examples/onnx-export.ipynb/0 | {
"file_path": "notebooks/examples/onnx-export.ipynb",
"repo_id": "notebooks",
"token_count": 6241
} | 150 |
<jupyter_start><jupyter_text>If you're opening this Notebook on colab, you will probably need to install the most recent versions of 🤗 Transformers and 🤗 Datasets. We will also need `scipy` and `scikit-learn` for some of the metrics. Uncomment the following cell and run it.<jupyter_code>#! pip install transformers
#!... | notebooks/examples/text_classification-tf.ipynb/0 | {
"file_path": "notebooks/examples/text_classification-tf.ipynb",
"repo_id": "notebooks",
"token_count": 8177
} | 151 |
<jupyter_start><jupyter_text><jupyter_code>!pip install transformers
!sudo apt-get install git-lfs
!git config --global user.email "julien@huggingface.co"
!git config --global user.name "Julien Chaumond"
!transformers-cli login
!pwd
!transformers-cli repo create policy-distilbert-7d
!git clone https://julien-c:...token... | notebooks/huggingface_hub/upload_hf_model.ipynb/0 | {
"file_path": "notebooks/huggingface_hub/upload_hf_model.ipynb",
"repo_id": "notebooks",
"token_count": 478
} | 152 |
import argparse
import logging
import os
import sys
import tensorflow as tf
from datasets import load_dataset
from tqdm import tqdm
from transformers import AutoTokenizer, TFAutoModelForSequenceClassification
from transformers.file_utils import is_sagemaker_dp_enabled
if os.environ.get("SDP_ENABLED") or is_sagemaker_... | notebooks/sagemaker/07_tensorflow_distributed_training_data_parallelism/scripts/train.py/0 | {
"file_path": "notebooks/sagemaker/07_tensorflow_distributed_training_data_parallelism/scripts/train.py",
"repo_id": "notebooks",
"token_count": 2936
} | 153 |
<jupyter_start><jupyter_text>HuggingFace Hub meets Amazon SageMaker Fine-tune a Multi-Class Classification with `Trainer` and `emotion` dataset and push it to the [Hugging Face Hub](https://huggingface.co/models) IntroductionWelcome to our end-to-end multi-class Text-Classification example. In this demo, we will use t... | notebooks/sagemaker/14_train_and_push_to_hub/sagemaker-notebook.ipynb/0 | {
"file_path": "notebooks/sagemaker/14_train_and_push_to_hub/sagemaker-notebook.ipynb",
"repo_id": "notebooks",
"token_count": 3921
} | 154 |
# 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... | notebooks/sagemaker/22_accelerate_sagemaker_examples/src/text-classification/train_using_s3_data.py/0 | {
"file_path": "notebooks/sagemaker/22_accelerate_sagemaker_examples/src/text-classification/train_using_s3_data.py",
"repo_id": "notebooks",
"token_count": 4657
} | 155 |
from transformers import DonutProcessor, VisionEncoderDecoderModel
import torch
device = "cuda" if torch.cuda.is_available() else "cpu"
def model_fn(model_dir):
# Load our model from Hugging Face
processor = DonutProcessor.from_pretrained(model_dir)
model = VisionEncoderDecoderModel.from_pretrained(model_... | notebooks/sagemaker/26_document_ai_donut/scripts/inference.py/0 | {
"file_path": "notebooks/sagemaker/26_document_ai_donut/scripts/inference.py",
"repo_id": "notebooks",
"token_count": 571
} | 156 |
<!--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 applicable law or agreed... | peft/docs/source/conceptual_guides/adapter.md/0 | {
"file_path": "peft/docs/source/conceptual_guides/adapter.md",
"repo_id": "peft",
"token_count": 2203
} | 157 |
<!--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 applicable law or agreed... | peft/docs/source/task_guides/image_classification_lora.md/0 | {
"file_path": "peft/docs/source/task_guides/image_classification_lora.md",
"repo_id": "peft",
"token_count": 4628
} | 158 |
<jupyter_start><jupyter_code>from datasets import load_dataset
from transformers import set_seed, AutoModelForSeq2SeqLM, AutoTokenizer
from peft import get_peft_model, MultitaskPromptTuningConfig, TaskType, MultitaskPromptTuningInit
set_seed(42)
model_name = "google/flan-t5-base"
peft_config = MultitaskPromptTuningC... | peft/examples/conditional_generation/multitask_prompt_tuning.ipynb/0 | {
"file_path": "peft/examples/conditional_generation/multitask_prompt_tuning.ipynb",
"repo_id": "peft",
"token_count": 3341
} | 159 |
<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 an image classification model by ONLY using **0.77%** of the original trainable parameters of the model. LoRA adds low-rank "update matrices" to certain blocks in the un... | peft/examples/image_classification/image_classification_peft_lora.ipynb/0 | {
"file_path": "peft/examples/image_classification/image_classification_peft_lora.ipynb",
"repo_id": "peft",
"token_count": 6369
} | 160 |
import argparse
import gc
import hashlib
import itertools
import logging
import math
import os
import threading
import warnings
from contextlib import nullcontext
from pathlib import Path
from typing import Optional
import datasets
import diffusers
import numpy as np
import psutil
import torch
import torch.nn.function... | peft/examples/lora_dreambooth/train_dreambooth.py/0 | {
"file_path": "peft/examples/lora_dreambooth/train_dreambooth.py",
"repo_id": "peft",
"token_count": 20213
} | 161 |
import argparse
import json
import logging
import os
from collections import Counter
from dataclasses import dataclass
from operator import attrgetter
from typing import Dict, List, Optional, Union
import safetensors
import torch
import torch.nn as nn
from diffusers import UNet2DConditionModel
from transformers import... | peft/examples/stable_diffusion/convert_sd_adapter_to_peft.py/0 | {
"file_path": "peft/examples/stable_diffusion/convert_sd_adapter_to_peft.py",
"repo_id": "peft",
"token_count": 10396
} | 162 |
# coding=utf-8
# 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 ap... | peft/src/peft/mixed_model.py/0 | {
"file_path": "peft/src/peft/mixed_model.py",
"repo_id": "peft",
"token_count": 6709
} | 163 |
# coding=utf-8
# 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 ap... | peft/src/peft/tuners/ia3/bnb.py/0 | {
"file_path": "peft/src/peft/tuners/ia3/bnb.py",
"repo_id": "peft",
"token_count": 2200
} | 164 |
# coding=utf-8
# 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 ap... | peft/src/peft/tuners/lora/layer.py/0 | {
"file_path": "peft/src/peft/tuners/lora/layer.py",
"repo_id": "peft",
"token_count": 14016
} | 165 |
# flake8: noqa
# There's no way to ignore "F401 '...' imported but unused" warnings in this
# module, but to preserve other warnings. So, don't check this module at all
# coding=utf-8
# Copyright 2023-present the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not u... | peft/src/peft/utils/peft_types.py/0 | {
"file_path": "peft/src/peft/utils/peft_types.py",
"repo_id": "peft",
"token_count": 851
} | 166 |
#!/usr/bin/env python3
# coding=utf-8
# 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
#... | peft/tests/test_lora_megatron.py/0 | {
"file_path": "peft/tests/test_lora_megatron.py",
"repo_id": "peft",
"token_count": 3000
} | 167 |
#!/usr/bin/env python3
""" Checkpoint Averaging Script
This script averages all model weights for checkpoints in specified path that match
the specified filter wildcard. All checkpoints must be from the exact same model.
For any hope of decent results, the checkpoints should be from the same or child
(via resumes) tr... | pytorch-image-models/avg_checkpoints.py/0 | {
"file_path": "pytorch-image-models/avg_checkpoints.py",
"repo_id": "pytorch-image-models",
"token_count": 2377
} | 168 |
# Adversarial Inception v3
**Inception v3** is a convolutional neural network architecture from the Inception family that makes several improvements including using [Label Smoothing](https://paperswithcode.com/method/label-smoothing), Factorized 7 x 7 convolutions, and the use of an [auxiliary classifer](https://paper... | pytorch-image-models/docs/models/.templates/models/adversarial-inception-v3.md/0 | {
"file_path": "pytorch-image-models/docs/models/.templates/models/adversarial-inception-v3.md",
"repo_id": "pytorch-image-models",
"token_count": 1432
} | 169 |
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