text stringlengths 7 328k | id stringlengths 14 166 | metadata dict | __index_level_0__ int64 0 471 |
|---|---|---|---|
# This first_section was backported from nginx
loading_datasets: loading
share_dataset: share
quicktour: quickstart
dataset_streaming: stream
torch_tensorflow: use_dataset
splits: loading#slice-splits
processing: process
faiss_and_ea: faiss_es
features: about_dataset_features
using_metrics: how_to_metrics
exploring: ac... | datasets/docs/source/_redirects.yml/0 | {
"file_path": "datasets/docs/source/_redirects.yml",
"repo_id": "datasets",
"token_count": 134
} | 63 |
# Create a dataset card
Each dataset should have a dataset card to promote responsible usage and inform users of any potential biases within the dataset.
This idea was inspired by the Model Cards proposed by [Mitchell, 2018](https://arxiv.org/abs/1810.03993).
Dataset cards help users understand a dataset's contents, t... | datasets/docs/source/dataset_card.mdx/0 | {
"file_path": "datasets/docs/source/dataset_card.mdx",
"repo_id": "datasets",
"token_count": 757
} | 64 |
# Load
Your data can be stored in various places; they can be on your local machine's disk, in a Github repository, and in in-memory data structures like Python dictionaries and Pandas DataFrames. Wherever a dataset is stored, 🤗 Datasets can help you load it.
This guide will show you how to load a dataset from:
- T... | datasets/docs/source/loading.mdx/0 | {
"file_path": "datasets/docs/source/loading.mdx",
"repo_id": "datasets",
"token_count": 7158
} | 65 |
# Stream
Dataset streaming lets you work with a dataset without downloading it.
The data is streamed as you iterate over the dataset.
This is especially helpful when:
- You don't want to wait for an extremely large dataset to download.
- The dataset size exceeds the amount of available disk space on your computer.
- ... | datasets/docs/source/stream.mdx/0 | {
"file_path": "datasets/docs/source/stream.mdx",
"repo_id": "datasets",
"token_count": 5324
} | 66 |
# 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/bleu/bleu.py/0 | {
"file_path": "datasets/metrics/bleu/bleu.py",
"repo_id": "datasets",
"token_count": 2139
} | 67 |
# Metric Card for CUAD
## Metric description
This metric wraps the official scoring script for version 1 of the [Contract Understanding Atticus Dataset (CUAD)](https://huggingface.co/datasets/cuad), which is a corpus of more than 13,000 labels in 510 commercial legal contracts that have been manually labeled to ident... | datasets/metrics/cuad/README.md/0 | {
"file_path": "datasets/metrics/cuad/README.md",
"repo_id": "datasets",
"token_count": 2380
} | 68 |
# Copyright 2022 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/mae/mae.py/0 | {
"file_path": "datasets/metrics/mae/mae.py",
"repo_id": "datasets",
"token_count": 1662
} | 69 |
# Copyright 2022 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/perplexity/perplexity.py/0 | {
"file_path": "datasets/metrics/perplexity/perplexity.py",
"repo_id": "datasets",
"token_count": 3550
} | 70 |
# Copyright 2021 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/spearmanr/spearmanr.py/0 | {
"file_path": "datasets/metrics/spearmanr/spearmanr.py",
"repo_id": "datasets",
"token_count": 1942
} | 71 |
# Metric Card for XNLI
## Metric description
The XNLI metric allows to evaluate a model's score on the [XNLI dataset](https://huggingface.co/datasets/xnli), which is a subset of a few thousand examples from the [MNLI dataset](https://huggingface.co/datasets/glue/viewer/mnli) that have been translated into a 14 differ... | datasets/metrics/xnli/README.md/0 | {
"file_path": "datasets/metrics/xnli/README.md",
"repo_id": "datasets",
"token_count": 1226
} | 72 |
#!/usr/bin/env python
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestComm... | datasets/src/datasets/commands/datasets_cli.py/0 | {
"file_path": "datasets/src/datasets/commands/datasets_cli.py",
"repo_id": "datasets",
"token_count": 473
} | 73 |
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.download_config import DownloadConfig
from ..download.streaming_download_manager import xopen, ... | datasets/src/datasets/features/audio.py/0 | {
"file_path": "datasets/src/datasets/features/audio.py",
"repo_id": "datasets",
"token_count": 5335
} | 74 |
# 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/src/datasets/inspect.py/0 | {
"file_path": "datasets/src/datasets/inspect.py",
"repo_id": "datasets",
"token_count": 9937
} | 75 |
# 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/splits.py/0 | {
"file_path": "datasets/src/datasets/splits.py",
"repo_id": "datasets",
"token_count": 9598
} | 76 |
import os
from apache_beam.io.filesystems import FileSystems
from apache_beam.pipeline import Pipeline
from .logging import get_logger
CHUNK_SIZE = 2 << 20 # 2mb
logger = get_logger(__name__)
class BeamPipeline(Pipeline):
"""Wrapper over `apache_beam.pipeline.Pipeline` for convenience"""
def is_local(se... | datasets/src/datasets/utils/beam_utils.py/0 | {
"file_path": "datasets/src/datasets/utils/beam_utils.py",
"repo_id": "datasets",
"token_count": 847
} | 77 |
{
"language": [
"found",
"crowdsourced",
"expert-generated",
"machine-generated",
"other"
],
"annotations": [
"found",
"crowdsourced",
"expert-generated",
"machine-generated",
"no-annotation",
"other"
]
}
| datasets/src/datasets/utils/resources/creators.json/0 | {
"file_path": "datasets/src/datasets/utils/resources/creators.json",
"repo_id": "datasets",
"token_count": 119
} | 78 |
## Add Dummy data test
**Important** In order to pass the `load_dataset_<dataset_name>` test, dummy data is required for all possible config names.
First we distinguish between datasets scripts that
- A) have no config class and
- B) have a config class
For A) the dummy data folder structure, will always look as fol... | datasets/tests/README.md/0 | {
"file_path": "datasets/tests/README.md",
"repo_id": "datasets",
"token_count": 928
} | 79 |
import os
import random
import tempfile
import unittest
import numpy as np
import pandas as pd
import pyarrow as pa
import pytest
from absl.testing import parameterized
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features import Array2D, Array3D, Array4D, Array5D, Value
from datasets.f... | datasets/tests/features/test_array_xd.py/0 | {
"file_path": "datasets/tests/features/test_array_xd.py",
"repo_id": "datasets",
"token_count": 9826
} | 80 |
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def _check_text_dataset(dataset, expected_features):
assert isinstance(dataset, Dataset)
... | datasets/tests/io/test_text.py/0 | {
"file_path": "datasets/tests/io/test_text.py",
"repo_id": "datasets",
"token_count": 1833
} | 81 |
import copy
import os
from pathlib import Path
from typing import List
from unittest.mock import patch
import fsspec
import pytest
from fsspec.registry import _registry as _fsspec_registry
from fsspec.spec import AbstractFileSystem
from datasets.data_files import (
DataFilesDict,
DataFilesList,
DataFilesP... | datasets/tests/test_data_files.py/0 | {
"file_path": "datasets/tests/test_data_files.py",
"repo_id": "datasets",
"token_count": 12329
} | 82 |
import os
from pathlib import Path
import pytest
from datasets.inspect import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_default_config_name,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
from datasets.packaged_modules.csv import csv
... | datasets/tests/test_inspect.py/0 | {
"file_path": "datasets/tests/test_inspect.py",
"repo_id": "datasets",
"token_count": 2089
} | 83 |
from copy import deepcopy
from unittest.case import TestCase
import pytest
from datasets.arrow_dataset import Dataset
from datasets.features import Audio, ClassLabel, Features, Image, Sequence, Value
from datasets.info import DatasetInfo
from datasets.tasks import (
AudioClassification,
AutomaticSpeechRecogni... | datasets/tests/test_tasks.py/0 | {
"file_path": "datasets/tests/test_tasks.py",
"repo_id": "datasets",
"token_count": 4249
} | 84 |
# The “Deep” in Reinforcement Learning [[deep-rl]]
<Tip>
What we've talked about so far is Reinforcement Learning. But where does the "Deep" come into play?
</Tip>
Deep Reinforcement Learning introduces **deep neural networks to solve Reinforcement Learning problems** — hence the name “deep”.
For instance, in the ne... | deep-rl-class/units/en/unit1/deep-rl.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit1/deep-rl.mdx",
"repo_id": "deep-rl-class",
"token_count": 310
} | 85 |
# Introduction to Q-Learning [[introduction-q-learning]]
<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit3/thumbnail.jpg" alt="Unit 2 thumbnail" width="100%">
In the first unit of this class, we learned about Reinforcement Learning (RL), the RL process, and the ... | deep-rl-class/units/en/unit2/introduction.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit2/introduction.mdx",
"repo_id": "deep-rl-class",
"token_count": 466
} | 86 |
# Hands-on [[hands-on]]
<CourseFloatingBanner classNames="absolute z-10 right-0 top-0"
notebooks={[
{label: "Google Colab", value: "https://colab.research.google.com/github/huggingface/deep-rl-class/blob/main/notebooks/unit3/unit3.ipynb"}
]}
askForHelpUrl="http://hf.co/join/discor... | deep-rl-class/units/en/unit3/hands-on.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit3/hands-on.mdx",
"repo_id": "deep-rl-class",
"token_count": 5087
} | 87 |
# Hands-on
<CourseFloatingBanner classNames="absolute z-10 right-0 top-0"
notebooks={[
{label: "Google Colab", value: "https://colab.research.google.com/github/huggingface/deep-rl-class/blob/main/notebooks/unit5/unit5.ipynb"}
]}
askForHelpUrl="http://hf.co/join/discord" />
We learned what ML-Agents is and how ... | deep-rl-class/units/en/unit5/hands-on.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit5/hands-on.mdx",
"repo_id": "deep-rl-class",
"token_count": 5146
} | 88 |
# An introduction to Multi-Agents Reinforcement Learning (MARL)
## From single agent to multiple agents
In the first unit, we learned to train agents in a single-agent system. When our agent was alone in its environment: **it was not cooperating or collaborating with other agents**.
<figure>
<img src="https://huggin... | deep-rl-class/units/en/unit7/introduction-to-marl.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit7/introduction-to-marl.mdx",
"repo_id": "deep-rl-class",
"token_count": 982
} | 89 |
# How Huggy works [[how-huggy-works]]
Huggy is a Deep Reinforcement Learning environment made by Hugging Face and based on [Puppo the Corgi, a project by the Unity MLAgents team](https://blog.unity.com/technology/puppo-the-corgi-cuteness-overload-with-the-unity-ml-agents-toolkit).
This environment was created using th... | deep-rl-class/units/en/unitbonus1/how-huggy-works.mdx/0 | {
"file_path": "deep-rl-class/units/en/unitbonus1/how-huggy-works.mdx",
"repo_id": "deep-rl-class",
"token_count": 1245
} | 90 |
# Offline vs. Online Reinforcement Learning
Deep Reinforcement Learning (RL) is a framework **to build decision-making agents**. These agents aim to learn optimal behavior (policy) by interacting with the environment through **trial and error and receiving rewards as unique feedback**.
The agent’s goal **is to maximi... | deep-rl-class/units/en/unitbonus3/offline-online.mdx/0 | {
"file_path": "deep-rl-class/units/en/unitbonus3/offline-online.mdx",
"repo_id": "deep-rl-class",
"token_count": 708
} | 91 |
FROM ubuntu:20.04
LABEL maintainer="Hugging Face"
LABEL repository="diffusers"
ENV DEBIAN_FRONTEND=noninteractive
RUN apt update && \
apt install -y bash \
build-essential \
git \
git-lfs \
curl \
ca-certificates \
... | diffusers/docker/diffusers-onnxruntime-cpu/Dockerfile/0 | {
"file_path": "diffusers/docker/diffusers-onnxruntime-cpu/Dockerfile",
"repo_id": "diffusers",
"token_count": 642
} | 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/loaders/lora.md/0 | {
"file_path": "diffusers/docs/source/en/api/loaders/lora.md",
"repo_id": "diffusers",
"token_count": 463
} | 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... | diffusers/docs/source/en/api/pipelines/controlnet.md/0 | {
"file_path": "diffusers/docs/source/en/api/pipelines/controlnet.md",
"repo_id": "diffusers",
"token_count": 1146
} | 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/overview.md/0 | {
"file_path": "diffusers/docs/source/en/api/pipelines/overview.md",
"repo_id": "diffusers",
"token_count": 1909
} | 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/api/pipelines/stable_diffusion/k_diffusion.md/0 | {
"file_path": "diffusers/docs/source/en/api/pipelines/stable_diffusion/k_diffusion.md",
"repo_id": "diffusers",
"token_count": 379
} | 96 |
<!--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/opt_overview.md/0 | {
"file_path": "diffusers/docs/source/en/optimization/opt_overview.md",
"repo_id": "diffusers",
"token_count": 353
} | 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/training/lora.md/0 | {
"file_path": "diffusers/docs/source/en/training/lora.md",
"repo_id": "diffusers",
"token_count": 3336
} | 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/control_brightness.md/0 | {
"file_path": "diffusers/docs/source/en/using-diffusers/control_brightness.md",
"repo_id": "diffusers",
"token_count": 874
} | 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/loading.md/0 | {
"file_path": "diffusers/docs/source/en/using-diffusers/loading.md",
"repo_id": "diffusers",
"token_count": 10373
} | 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/en/using-diffusers/text-img2vid.md/0 | {
"file_path": "diffusers/docs/source/en/using-diffusers/text-img2vid.md",
"repo_id": "diffusers",
"token_count": 7527
} | 101 |
# 학습을 위한 데이터셋 만들기
[Hub](https://huggingface.co/datasets?task_categories=task_categories:text-to-image&sort=downloads) 에는 모델 교육을 위한 많은 데이터셋이 있지만,
관심이 있거나 사용하고 싶은 데이터셋을 찾을 수 없는 경우 🤗 [Datasets](hf.co/docs/datasets) 라이브러리를 사용하여 데이터셋을 만들 수 있습니다.
데이터셋 구조는 모델을 학습하려는 작업에 따라 달라집니다.
가장 기본적인 데이터셋 구조는 unconditional 이미지 생성과 같은 작업... | diffusers/docs/source/ko/training/create_dataset.md/0 | {
"file_path": "diffusers/docs/source/ko/training/create_dataset.md",
"repo_id": "diffusers",
"token_count": 3214
} | 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/using-diffusers/custom_pipeline_examples.md/0 | {
"file_path": "diffusers/docs/source/ko/using-diffusers/custom_pipeline_examples.md",
"repo_id": "diffusers",
"token_count": 10864
} | 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/weighted_prompts.md/0 | {
"file_path": "diffusers/docs/source/ko/using-diffusers/weighted_prompts.md",
"repo_id": "diffusers",
"token_count": 3375
} | 104 |
## Amused training
Amused can be finetuned on simple datasets relatively cheaply and quickly. Using 8bit optimizers, lora, and gradient accumulation, amused can be finetuned with as little as 5.5 GB. Here are a set of examples for finetuning amused on some relatively simple datasets. These training recipies are aggres... | diffusers/examples/amused/README.md/0 | {
"file_path": "diffusers/examples/amused/README.md",
"repo_id": "diffusers",
"token_count": 5921
} | 105 |
"""
modeled after the textual_inversion.py / train_dreambooth.py and the work
of justinpinkney here: https://github.com/justinpinkney/stable-diffusion/blob/main/notebooks/imagic.ipynb
"""
import inspect
import warnings
from typing import List, Optional, Union
import numpy as np
import PIL.Image
import torch
import to... | diffusers/examples/community/imagic_stable_diffusion.py/0 | {
"file_path": "diffusers/examples/community/imagic_stable_diffusion.py",
"repo_id": "diffusers",
"token_count": 9827
} | 106 |
import inspect
from copy import deepcopy
from enum import Enum
from typing import List, Optional, Tuple, Union
import torch
from tqdm.auto import tqdm
from diffusers.models import AutoencoderKL, UNet2DConditionModel
from diffusers.pipelines.pipeline_utils import DiffusionPipeline
from diffusers.pipelines.stable_diffu... | diffusers/examples/community/mixture_tiling.py/0 | {
"file_path": "diffusers/examples/community/mixture_tiling.py",
"repo_id": "diffusers",
"token_count": 9146
} | 107 |
# Inspired by: https://github.com/Mikubill/sd-webui-controlnet/discussions/1236 and https://github.com/Mikubill/sd-webui-controlnet/discussions/1280
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import numpy as np
import PIL.Image
import torch
from diffusers import StableDiffusionControlNetPipe... | diffusers/examples/community/stable_diffusion_controlnet_reference.py/0 | {
"file_path": "diffusers/examples/community/stable_diffusion_controlnet_reference.py",
"repo_id": "diffusers",
"token_count": 21091
} | 108 |
# Latent Consistency Distillation Example:
[Latent Consistency Models (LCMs)](https://arxiv.org/abs/2310.04378) is a method to distill a latent diffusion model to enable swift inference with minimal steps. This example demonstrates how to use latent consistency distillation to distill stable-diffusion-v1.5 for inferen... | diffusers/examples/consistency_distillation/README.md/0 | {
"file_path": "diffusers/examples/consistency_distillation/README.md",
"repo_id": "diffusers",
"token_count": 1511
} | 109 |
#!/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/controlnet/train_controlnet_flax.py/0 | {
"file_path": "diffusers/examples/controlnet/train_controlnet_flax.py",
"repo_id": "diffusers",
"token_count": 20114
} | 110 |
import argparse
import logging
import math
import os
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 flax import jax_utils
from flax.training import train_state
from flax.training.common_utils import shard
f... | diffusers/examples/dreambooth/train_dreambooth_flax.py/0 | {
"file_path": "diffusers/examples/dreambooth/train_dreambooth_flax.py",
"repo_id": "diffusers",
"token_count": 11966
} | 111 |
# coding=utf-8
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | diffusers/examples/kandinsky2_2/text_to_image/train_text_to_image_lora_prior.py/0 | {
"file_path": "diffusers/examples/kandinsky2_2/text_to_image/train_text_to_image_lora_prior.py",
"repo_id": "diffusers",
"token_count": 15623
} | 112 |
# !pip install opencv-python transformers accelerate
import argparse
import cv2
import numpy as np
import torch
from controlnetxs import ControlNetXSModel
from PIL import Image
from pipeline_controlnet_xs import StableDiffusionControlNetXSPipeline
from diffusers.utils import load_image
parser = argparse.ArgumentPar... | diffusers/examples/research_projects/controlnetxs/infer_sd_controlnetxs.py/0 | {
"file_path": "diffusers/examples/research_projects/controlnetxs/infer_sd_controlnetxs.py",
"repo_id": "diffusers",
"token_count": 646
} | 113 |
# InstructPix2Pix text-to-edit-image fine-tuning
This extended LoRA training script was authored by [Aiden-Frost](https://github.com/Aiden-Frost).
This is an experimental LoRA extension of [this example](https://github.com/huggingface/diffusers/blob/main/examples/instruct_pix2pix/train_instruct_pix2pix.py). This script... | diffusers/examples/research_projects/instructpix2pix_lora/README.md/0 | {
"file_path": "diffusers/examples/research_projects/instructpix2pix_lora/README.md",
"repo_id": "diffusers",
"token_count": 1124
} | 114 |
import argparse
import itertools
import json
import logging
import math
import uuid
import warnings
from os import environ, listdir, makedirs
from os.path import basename, join
from pathlib import Path
from typing import List
import datasets
import numpy as np
import torch
import torch.nn.functional as F
import torch.... | diffusers/examples/research_projects/multi_subject_dreambooth/train_multi_subject_dreambooth.py/0 | {
"file_path": "diffusers/examples/research_projects/multi_subject_dreambooth/train_multi_subject_dreambooth.py",
"repo_id": "diffusers",
"token_count": 21771
} | 115 |
# 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
} | 116 |
#!/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_flax.py/0 | {
"file_path": "diffusers/examples/text_to_image/train_text_to_image_flax.py",
"repo_id": "diffusers",
"token_count": 10030
} | 117 |
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": 13300
} | 118 |
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
} | 119 |
# coding=utf-8
# Copyright 2024, 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
} | 120 |
import argparse
import os
import shutil
from pathlib import Path
import onnx
import onnx_graphsurgeon as gs
import torch
from onnx import shape_inference
from packaging import version
from polygraphy.backend.onnx.loader import fold_constants
from torch.onnx import export
from diffusers import (
ControlNetModel,
... | diffusers/scripts/convert_stable_diffusion_controlnet_to_onnx.py/0 | {
"file_path": "diffusers/scripts/convert_stable_diffusion_controlnet_to_onnx.py",
"repo_id": "diffusers",
"token_count": 8995
} | 121 |
# 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/loaders/lora.py/0 | {
"file_path": "diffusers/src/diffusers/loaders/lora.py",
"repo_id": "diffusers",
"token_count": 31234
} | 122 |
from .autoencoder_asym_kl import AsymmetricAutoencoderKL
from .autoencoder_kl import AutoencoderKL
from .autoencoder_kl_temporal_decoder import AutoencoderKLTemporalDecoder
from .autoencoder_tiny import AutoencoderTiny
from .consistency_decoder_vae import ConsistencyDecoderVAE
| diffusers/src/diffusers/models/autoencoders/__init__.py/0 | {
"file_path": "diffusers/src/diffusers/models/autoencoders/__init__.py",
"repo_id": "diffusers",
"token_count": 99
} | 123 |
from dataclasses import dataclass
from ..utils import BaseOutput
@dataclass
class AutoencoderKLOutput(BaseOutput):
"""
Output of AutoencoderKL encoding method.
Args:
latent_dist (`DiagonalGaussianDistribution`):
Encoded outputs of `Encoder` represented as the mean and logvar of `Diag... | diffusers/src/diffusers/models/modeling_outputs.py/0 | {
"file_path": "diffusers/src/diffusers/models/modeling_outputs.py",
"repo_id": "diffusers",
"token_count": 178
} | 124 |
# 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_kandinsky3.py/0 | {
"file_path": "diffusers/src/diffusers/models/unets/unet_kandinsky3.py",
"repo_id": "diffusers",
"token_count": 9647
} | 125 |
from typing import TYPE_CHECKING
from ...utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
get_objects_from_module,
is_flax_available,
is_torch_available,
is_transformers_available,
)
_dummy_objects = {}
_import_structure = {}
try:
if not (is_transfor... | diffusers/src/diffusers/pipelines/controlnet/__init__.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/controlnet/__init__.py",
"repo_id": "diffusers",
"token_count": 1294
} | 126 |
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 = {
"timesteps": [
"fast27_timesteps",
... | diffusers/src/diffusers/pipelines/deepfloyd_if/__init__.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/deepfloyd_if/__init__.py",
"repo_id": "diffusers",
"token_count": 1266
} | 127 |
# Copyright 2022 The Music Spectrogram Diffusion Authors.
# 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... | diffusers/src/diffusers/pipelines/deprecated/spectrogram_diffusion/notes_encoder.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/deprecated/spectrogram_diffusion/notes_encoder.py",
"repo_id": "diffusers",
"token_count": 1254
} | 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/deprecated/versatile_diffusion/pipeline_versatile_diffusion_text_to_image.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/deprecated/versatile_diffusion/pipeline_versatile_diffusion_text_to_image.py",
"repo_id": "diffusers",
"token_count": 9810
} | 129 |
# 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.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/kandinsky2_2/pipeline_kandinsky2_2.py",
"repo_id": "diffusers",
"token_count": 6269
} | 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/latent_diffusion/pipeline_latent_diffusion.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion.py",
"repo_id": "diffusers",
"token_count": 14315
} | 131 |
# coding=utf-8
# Copyright 2024 The HuggingFace Inc. team.
# Copyright (c) 2022, NVIDIA CORPORATION. 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.a... | diffusers/src/diffusers/pipelines/pipeline_utils.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/pipeline_utils.py",
"repo_id": "diffusers",
"token_count": 40780
} | 132 |
from typing import TYPE_CHECKING
from ...utils import (
DIFFUSERS_SLOW_IMPORT,
OptionalDependencyNotAvailable,
_LazyModule,
get_objects_from_module,
is_flax_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_onnx_available,
is_torch_available,
is_transformers_availa... | diffusers/src/diffusers/pipelines/stable_diffusion/__init__.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/stable_diffusion/__init__.py",
"repo_id": "diffusers",
"token_count": 3769
} | 133 |
# Copyright 2024 The InstructPix2Pix Authors 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/pipelines/stable_diffusion/pipeline_stable_diffusion_instruct_pix2pix.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_instruct_pix2pix.py",
"repo_id": "diffusers",
"token_count": 17595
} | 134 |
# 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_k_diffusion/pipeline_stable_diffusion_k_diffusion.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/stable_diffusion_k_diffusion/pipeline_stable_diffusion_k_diffusion.py",
"repo_id": "diffusers",
"token_count": 14484
} | 135 |
# Copyright 2024 Kakao Brain 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 requi... | diffusers/src/diffusers/pipelines/unclip/pipeline_unclip.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/unclip/pipeline_unclip.py",
"repo_id": "diffusers",
"token_count": 9940
} | 136 |
# Schedulers
For more information on the schedulers, please refer to the [docs](https://huggingface.co/docs/diffusers/api/schedulers/overview). | diffusers/src/diffusers/schedulers/README.md/0 | {
"file_path": "diffusers/src/diffusers/schedulers/README.md",
"repo_id": "diffusers",
"token_count": 46
} | 137 |
# Copyright 2024 FLAIR Lab 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 require... | diffusers/src/diffusers/schedulers/scheduling_deis_multistep.py/0 | {
"file_path": "diffusers/src/diffusers/schedulers/scheduling_deis_multistep.py",
"repo_id": "diffusers",
"token_count": 15883
} | 138 |
# Copyright 2024 Stanford 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_lcm.py/0 | {
"file_path": "diffusers/src/diffusers/schedulers/scheduling_lcm.py",
"repo_id": "diffusers",
"token_count": 13433
} | 139 |
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | diffusers/src/diffusers/utils/__init__.py/0 | {
"file_path": "diffusers/src/diffusers/utils/__init__.py",
"repo_id": "diffusers",
"token_count": 1507
} | 140 |
# This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends
class SpectrogramDiffusionPipeline(metaclass=DummyObject):
_backends = ["transformers", "torch", "note_seq"]
def __init__(self, *args, **kwargs):
requires_backends(self, ["tr... | diffusers/src/diffusers/utils/dummy_transformers_and_torch_and_note_seq_objects.py/0 | {
"file_path": "diffusers/src/diffusers/utils/dummy_transformers_and_torch_and_note_seq_objects.py",
"repo_id": "diffusers",
"token_count": 236
} | 141 |
import inspect
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
@require_flax
class FlaxModelTesterMixin:
def test_output(self):
init_dict, inputs_dict = self.prepare_init_args_and_inputs_for_common()
mo... | diffusers/tests/models/test_modeling_common_flax.py/0 | {
"file_path": "diffusers/tests/models/test_modeling_common_flax.py",
"repo_id": "diffusers",
"token_count": 1124
} | 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/others/test_config.py/0 | {
"file_path": "diffusers/tests/others/test_config.py",
"repo_id": "diffusers",
"token_count": 4006
} | 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/controlnet/test_flax_controlnet.py/0 | {
"file_path": "diffusers/tests/pipelines/controlnet/test_flax_controlnet.py",
"repo_id": "diffusers",
"token_count": 2141
} | 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/kandinsky2_2/test_kandinsky_prior.py/0 | {
"file_path": "diffusers/tests/pipelines/kandinsky2_2/test_kandinsky_prior.py",
"repo_id": "diffusers",
"token_count": 4049
} | 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/stable_cascade/test_stable_cascade_decoder.py/0 | {
"file_path": "diffusers/tests/pipelines/stable_cascade/test_stable_cascade_decoder.py",
"repo_id": "diffusers",
"token_count": 5590
} | 146 |
# 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_flax.py/0 | {
"file_path": "diffusers/tests/pipelines/stable_diffusion_2/test_stable_diffusion_flax.py",
"repo_id": "diffusers",
"token_count": 1712
} | 147 |
import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNet2DConditionModel,
)
from diffusers.pipeline... | diffusers/tests/pipelines/stable_unclip/test_stable_unclip.py/0 | {
"file_path": "diffusers/tests/pipelines/stable_unclip/test_stable_unclip.py",
"repo_id": "diffusers",
"token_count": 4059
} | 148 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class DEISMultistepSchedulerTest(SchedulerCommonTest):
scheduler_classes = (DEISMul... | diffusers/tests/schedulers/test_scheduler_deis.py/0 | {
"file_path": "diffusers/tests/schedulers/test_scheduler_deis.py",
"repo_id": "diffusers",
"token_count": 5267
} | 149 |
import tempfile
import torch
from diffusers import PNDMScheduler
from .test_schedulers import SchedulerCommonTest
class PNDMSchedulerTest(SchedulerCommonTest):
scheduler_classes = (PNDMScheduler,)
forward_default_kwargs = (("num_inference_steps", 50),)
def get_scheduler_config(self, **kwargs):
... | diffusers/tests/schedulers/test_scheduler_pndm.py/0 | {
"file_path": "diffusers/tests/schedulers/test_scheduler_pndm.py",
"repo_id": "diffusers",
"token_count": 4654
} | 150 |
# coding=utf-8
# Copyright 2024 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requir... | diffusers/utils/fetch_latest_release_branch.py/0 | {
"file_path": "diffusers/utils/fetch_latest_release_branch.py",
"repo_id": "diffusers",
"token_count": 824
} | 151 |
<jupyter_start><jupyter_text>Making a Class-Conditioned Diffusion ModelIn this notebook we're going to illustrate one way to add conditioning information to a diffusion model. Specifically, we'll train a class-conditioned diffusion model on MNIST following on from the ['from-scratch' example in Unit 1](https://github.c... | diffusion-models-class/unit2/02_class_conditioned_diffusion_model_example.ipynb/0 | {
"file_path": "diffusion-models-class/unit2/02_class_conditioned_diffusion_model_example.ipynb",
"repo_id": "diffusion-models-class",
"token_count": 3041
} | 152 |
<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
} | 153 |
<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
} | 154 |
<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
} | 155 |
<jupyter_start><jupyter_text>In-painting pipeline for Stable Diffusion using 🧨 Diffusers This notebook shows how to do text-guided in-painting with Stable Diffusion model using 🤗 Hugging Face [🧨 Diffusers library](https://github.com/huggingface/diffusers). For a general introduction to the Stable Diffusion model pl... | notebooks/diffusers/in_painting_with_stable_diffusion_using_diffusers.ipynb/0 | {
"file_path": "notebooks/diffusers/in_painting_with_stable_diffusion_using_diffusers.ipynb",
"repo_id": "notebooks",
"token_count": 1254
} | 156 |
# IDEFICS Demos/examples
## Inference
- [Normal inference](inference.py) (needs ~20GB GPU memory)
- [4bit quantized inference](inference_4bit.py) (needs ~7GB GPU memory)
## Finetuning
The following demos use the Image captioning task:
- [PEFT (LORA) finetuning (notebook)](finetune_image_captioning_peft.ipynb) (fits... | notebooks/examples/idefics/README.md/0 | {
"file_path": "notebooks/examples/idefics/README.md",
"repo_id": "notebooks",
"token_count": 148
} | 157 |
<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<jupyter_output><empty_outpu... | notebooks/examples/nucleotide_transformer_dna_sequence_modelling.ipynb/0 | {
"file_path": "notebooks/examples/nucleotide_transformer_dna_sequence_modelling.ipynb",
"repo_id": "notebooks",
"token_count": 6637
} | 158 |
<jupyter_start><jupyter_text>If you're opening this Notebook on colab, you will probably need to install 🤗 Transformers and 🤗 Datasets as well as other dependencies. Uncomment the following cell and run it.<jupyter_code>#! pip install datasets evaluate transformers rouge-score nltk<jupyter_output><empty_output><jupyt... | notebooks/examples/summarization.ipynb/0 | {
"file_path": "notebooks/examples/summarization.ipynb",
"repo_id": "notebooks",
"token_count": 5127
} | 159 |
<jupyter_start><jupyter_text>Fine-tuning for Video Classification with 🤗 TransformersThis notebook shows how to fine-tune a pre-trained Vision model for Video Classification on a custom dataset. The idea is to add a randomly initialized classification head on top of a pre-trained encoder and fine-tune the model altoge... | notebooks/examples/video_classification.ipynb/0 | {
"file_path": "notebooks/examples/video_classification.ipynb",
"repo_id": "notebooks",
"token_count": 8881
} | 160 |
<jupyter_start><jupyter_text>Huggingface Sagemaker-sdk - training with custom metrics Binary Classification with `Trainer` and `imdb` dataset In this demo, we extend the basic classification demo by adding **metrics definition** to capture and visualize training metrics.The documentation of the SageMaker metrics captur... | notebooks/sagemaker/06_sagemaker_metrics/sagemaker-notebook.ipynb/0 | {
"file_path": "notebooks/sagemaker/06_sagemaker_metrics/sagemaker-notebook.ipynb",
"repo_id": "notebooks",
"token_count": 3000
} | 161 |
<jupyter_start><jupyter_text>Going Production: Auto-scale Hugging Face Transformer Endpoints with Amazon SageMaker Welcome to this getting started guide, we will use the new Hugging Face Inference DLCs and Amazon SageMaker Python SDK to deploy a transformer model for real-time inference. In this example we are going to... | notebooks/sagemaker/13_deploy_and_autoscaling_transformers/sagemaker-notebook.ipynb/0 | {
"file_path": "notebooks/sagemaker/13_deploy_and_autoscaling_transformers/sagemaker-notebook.ipynb",
"repo_id": "notebooks",
"token_count": 2793
} | 162 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.