text stringlengths 7 318k | id stringlengths 14 166 | metadata dict | __index_level_0__ int64 0 439 |
|---|---|---|---|
import { collections } from "$lib/server/database";
import { type Actions, fail, redirect } from "@sveltejs/kit";
import { ObjectId } from "mongodb";
import { authCondition } from "$lib/server/auth";
import { base } from "$app/paths";
async function assistantOnlyIfAuthor(locals: App.Locals, assistantId?: string) {
co... | chat-ui/src/routes/settings/assistants/[assistantId]/+page.server.ts/0 | {
"file_path": "chat-ui/src/routes/settings/assistants/[assistantId]/+page.server.ts",
"repo_id": "chat-ui",
"token_count": 1257
} | 52 |
{
"$schema": "https://vega.github.io/schema/vega-lite/v4.json",
"data": {
"values": "<DVC_METRIC_DATA>"
},
"title": "<DVC_METRIC_TITLE>",
"mark": {
"type": "line"
},
"encoding": {
"x": {
"field": "<DVC_METRIC_X>",
"type": "quantitative",
... | datasets/.dvc/plots/smooth.json/0 | {
"file_path": "datasets/.dvc/plots/smooth.json",
"repo_id": "datasets",
"token_count": 569
} | 53 |
.PHONY: quality style test
check_dirs := tests src benchmarks metrics utils
# Check that source code meets quality standards
quality:
ruff check $(check_dirs) setup.py # linter
ruff format --check $(check_dirs) setup.py # formatter
# Format source code automatically
style:
ruff check --fix $(check_dirs) setup.... | datasets/Makefile/0 | {
"file_path": "datasets/Makefile",
"repo_id": "datasets",
"token_count": 149
} | 54 |
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def get_duration(func):
def wrapper(*args, **kwargs):
starttime = timeit.default_timer()
_ = func(*args, **kwargs)
delta = timeit.default_timer()... | datasets/benchmarks/utils.py/0 | {
"file_path": "datasets/benchmarks/utils.py",
"repo_id": "datasets",
"token_count": 927
} | 55 |
# Beam Datasets
Some datasets are too large to be processed on a single machine. Instead, you can process them with [Apache Beam](https://beam.apache.org/), a library for parallel data processing. The processing pipeline is executed on a distributed processing backend such as [Apache Flink](https://flink.apache.org/),... | datasets/docs/source/beam.mdx/0 | {
"file_path": "datasets/docs/source/beam.mdx",
"repo_id": "datasets",
"token_count": 562
} | 56 |
# Datasets
<img class="float-left !m-0 !border-0 !dark:border-0 !shadow-none !max-w-lg w-[150px]" src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/datasets/datasets_logo.png"/>
🤗 Datasets is a library for easily accessing and sharing datasets for Audio, Computer Vision, and Natural ... | datasets/docs/source/index.mdx/0 | {
"file_path": "datasets/docs/source/index.mdx",
"repo_id": "datasets",
"token_count": 1014
} | 57 |
# Structure your repository
To host and share your dataset, create a dataset repository on the Hugging Face Hub and upload your data files.
This guide will show you how to structure your dataset repository when you upload it.
A dataset with a supported structure and file format (`.txt`, `.csv`, `.parquet`, `.jsonl`, ... | datasets/docs/source/repository_structure.mdx/0 | {
"file_path": "datasets/docs/source/repository_structure.mdx",
"repo_id": "datasets",
"token_count": 2588
} | 58 |
# Metric Card for BERT Score
## Metric description
BERTScore is an automatic evaluation metric for text generation that computes a similarity score for each token in the candidate sentence with each token in the reference sentence. It leverages the pre-trained contextual embeddings from [BERT](https://huggingface.co/... | datasets/metrics/bertscore/README.md/0 | {
"file_path": "datasets/metrics/bertscore/README.md",
"repo_id": "datasets",
"token_count": 1908
} | 59 |
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.... | datasets/metrics/competition_math/competition_math.py/0 | {
"file_path": "datasets/metrics/competition_math/competition_math.py",
"repo_id": "datasets",
"token_count": 1181
} | 60 |
# Metric Card for IndicGLUE
## Metric description
This metric is used to compute the evaluation metric for the [IndicGLUE dataset](https://huggingface.co/datasets/indic_glue).
IndicGLUE is a natural language understanding benchmark for Indian languages. It contains a wide variety of tasks and covers 11 major Indian ... | datasets/metrics/indic_glue/README.md/0 | {
"file_path": "datasets/metrics/indic_glue/README.md",
"repo_id": "datasets",
"token_count": 1527
} | 61 |
# Metric Card for Pearson Correlation Coefficient (pearsonr)
## Metric Description
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies on the assumption that each data... | datasets/metrics/pearsonr/README.md/0 | {
"file_path": "datasets/metrics/pearsonr/README.md",
"repo_id": "datasets",
"token_count": 1387
} | 62 |
# Metric Card for seqeval
## Metric description
seqeval is a Python framework for sequence labeling evaluation. seqeval can evaluate the performance of chunking tasks such as named-entity recognition, part-of-speech tagging, semantic role labeling and so on.
## How to use
Seqeval produces labelling scores along ... | datasets/metrics/seqeval/README.md/0 | {
"file_path": "datasets/metrics/seqeval/README.md",
"repo_id": "datasets",
"token_count": 2355
} | 63 |
# Copyright 2021 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/wer/wer.py/0 | {
"file_path": "datasets/metrics/wer/wer.py",
"repo_id": "datasets",
"token_count": 1452
} | 64 |
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenate_iterable_datasets, _interle... | datasets/src/datasets/combine.py/0 | {
"file_path": "datasets/src/datasets/combine.py",
"repo_id": "datasets",
"token_count": 4607
} | 65 |
import glob
import io
import os
import posixpath
import re
import tarfile
import time
import xml.dom.minidom
import zipfile
from asyncio import TimeoutError
from io import BytesIO
from itertools import chain
from pathlib import Path, PurePosixPath
from typing import Any, Callable, Dict, Generator, Iterable, List, Optio... | datasets/src/datasets/download/streaming_download_manager.py/0 | {
"file_path": "datasets/src/datasets/download/streaming_download_manager.py",
"repo_id": "datasets",
"token_count": 18792
} | 66 |
# Copyright 2020 The HuggingFace 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 agreed to... | datasets/src/datasets/formatting/torch_formatter.py/0 | {
"file_path": "datasets/src/datasets/formatting/torch_formatter.py",
"repo_id": "datasets",
"token_count": 1679
} | 67 |
# 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/naming.py/0 | {
"file_path": "datasets/src/datasets/naming.py",
"repo_id": "datasets",
"token_count": 1178
} | 68 |
import contextlib
from multiprocessing import Pool, RLock
from tqdm.auto import tqdm
from ..utils import experimental, logging
logger = logging.get_logger(__name__)
class ParallelBackendConfig:
backend_name = None
@experimental
def parallel_map(function, iterable, num_proc, types, disable_tqdm, desc, single... | datasets/src/datasets/parallel/parallel.py/0 | {
"file_path": "datasets/src/datasets/parallel/parallel.py",
"repo_id": "datasets",
"token_count": 1700
} | 69 |
# 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... | datasets/src/datasets/utils/_dill.py/0 | {
"file_path": "datasets/src/datasets/utils/_dill.py",
"repo_id": "datasets",
"token_count": 8380
} | 70 |
# loading package files: https://stackoverflow.com/a/20885799
import importlib.resources as pkg_resources
import logging
from pathlib import Path
from typing import Any, List, Tuple
import yaml
from . import resources
from .deprecation_utils import deprecated
BASE_REF_URL = "https://github.com/huggingface/datasets/... | datasets/src/datasets/utils/readme.py/0 | {
"file_path": "datasets/src/datasets/utils/readme.py",
"repo_id": "datasets",
"token_count": 5742
} | 71 |
# Metric Card for *Current Metric*
***Metric Card Instructions:*** *Copy this file into the relevant metric folder, then fill it out and save it as README.md. Feel free to take a look at existing metric cards if you'd like examples.*
## Metric Description
*Give a brief overview of this metric.*
## How to Use
*Give g... | datasets/templates/metric_card_template.md/0 | {
"file_path": "datasets/templates/metric_card_template.md",
"repo_id": "datasets",
"token_count": 397
} | 72 |
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, IterableDatasetDict, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.info import DatasetInfo
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get... | datasets/tests/io/test_parquet.py/0 | {
"file_path": "datasets/tests/io/test_parquet.py",
"repo_id": "datasets",
"token_count": 3621
} | 73 |
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import datasets
import datasets.config
from .utils import require_beam
class DummyBeamDataset(datasets.BeamBasedBuilder):
"""Dummy beam dataset."""
def _info(self):
return datasets.... | datasets/tests/test_beam.py/0 | {
"file_path": "datasets/tests/test_beam.py",
"repo_id": "datasets",
"token_count": 3076
} | 74 |
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
"files",
[
["full:README.md", "dataset_infos.json"],
["empty:README.md", "dataset_infos.json"],
["dataset_infos... | datasets/tests/test_info.py/0 | {
"file_path": "datasets/tests/test_info.py",
"repo_id": "datasets",
"token_count": 2685
} | 75 |
import json
import os
import re
from pathlib import Path
import pytest
from fsspec.registry import _registry as _fsspec_registry
from fsspec.spec import AbstractBufferedFile, AbstractFileSystem
from datasets.download.download_config import DownloadConfig
from datasets.download.streaming_download_manager import (
... | datasets/tests/test_streaming_download_manager.py/0 | {
"file_path": "datasets/tests/test_streaming_download_manager.py",
"repo_id": "datasets",
"token_count": 17220
} | 76 |
# Setup [[setup]]
After all this information, it's time to get started. We're going to do two things:
1. **Create your Hugging Face account** if it's not already done
2. **Sign up to Discord and introduce yourself** (don't be shy 🤗)
### Let's create my Hugging Face account
(If it's not already done) create an acco... | deep-rl-class/units/en/unit0/setup.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit0/setup.mdx",
"repo_id": "deep-rl-class",
"token_count": 389
} | 77 |
# Conclusion [[conclusion]]
Congrats on finishing this chapter! There was a lot of information. And congrats on finishing the tutorials. You’ve just implemented your first RL agent from scratch and shared it on the Hub 🥳.
Implementing from scratch when you study a new architecture **is important to understand how it... | deep-rl-class/units/en/unit2/conclusion.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit2/conclusion.mdx",
"repo_id": "deep-rl-class",
"token_count": 337
} | 78 |
# The Deep Q-Network (DQN) [[deep-q-network]]
This is the architecture of our Deep Q-Learning network:
<img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit4/deep-q-network.jpg" alt="Deep Q Network"/>
As input, we take a **stack of 4 frames** passed through the netwo... | deep-rl-class/units/en/unit3/deep-q-network.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit3/deep-q-network.mdx",
"repo_id": "deep-rl-class",
"token_count": 888
} | 79 |
# Bonus: Learn to create your own environments with Unity and MLAgents
**You can create your own reinforcement learning environments with Unity and MLAgents**. Using a game engine such as Unity can be intimidating at first, but here are the steps you can take to learn smoothly.
## Step 1: Know how to use Unity
- The... | deep-rl-class/units/en/unit5/bonus.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit5/bonus.mdx",
"repo_id": "deep-rl-class",
"token_count": 360
} | 80 |
# Additional Readings [[additional-readings]]
## An introduction to multi-agents
- [Multi-agent reinforcement learning: An overview](https://www.dcsc.tudelft.nl/~bdeschutter/pub/rep/10_003.pdf)
- [Multiagent Reinforcement Learning, Marc Lanctot](https://rlss.inria.fr/files/2019/07/RLSS_Multiagent.pdf)
- [Example of ... | deep-rl-class/units/en/unit7/additional-readings.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit7/additional-readings.mdx",
"repo_id": "deep-rl-class",
"token_count": 432
} | 81 |
# The intuition behind PPO [[the-intuition-behind-ppo]]
The idea with Proximal Policy Optimization (PPO) is that we want to improve the training stability of the policy by limiting the change you make to the policy at each training epoch: **we want to avoid having too large of a policy update.**
For two reasons:
- W... | deep-rl-class/units/en/unit8/intuition-behind-ppo.mdx/0 | {
"file_path": "deep-rl-class/units/en/unit8/intuition-behind-ppo.mdx",
"repo_id": "deep-rl-class",
"token_count": 426
} | 82 |
# Language models in RL
## LMs encode useful knowledge for agents
**Language models** (LMs) can exhibit impressive abilities when manipulating text such as question-answering or even step-by-step reasoning. Additionally, their training on massive text corpora allowed them to **encode various types of knowledge includi... | deep-rl-class/units/en/unitbonus3/language-models.mdx/0 | {
"file_path": "deep-rl-class/units/en/unitbonus3/language-models.mdx",
"repo_id": "deep-rl-class",
"token_count": 1011
} | 83 |
.PHONY: deps_table_update modified_only_fixup extra_style_checks quality style fixup fix-copies test test-examples
# make sure to test the local checkout in scripts and not the pre-installed one (don't use quotes!)
export PYTHONPATH = src
check_dirs := examples scripts src tests utils benchmarks
modified_only_fixup:... | diffusers/Makefile/0 | {
"file_path": "diffusers/Makefile",
"repo_id": "diffusers",
"token_count": 889
} | 84 |
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": 630
} | 85 |
<!--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/loaders/lora.md/0 | {
"file_path": "diffusers/docs/source/en/api/loaders/lora.md",
"repo_id": "diffusers",
"token_count": 464
} | 86 |
<!--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/controlnet.md/0 | {
"file_path": "diffusers/docs/source/en/api/pipelines/controlnet.md",
"repo_id": "diffusers",
"token_count": 1147
} | 87 |
<!--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/paint_by_example.md/0 | {
"file_path": "diffusers/docs/source/en/api/pipelines/paint_by_example.md",
"repo_id": "diffusers",
"token_count": 763
} | 88 |
<!--Copyright 2023 The Intel Labs Team Authors and 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... | diffusers/docs/source/en/api/pipelines/stable_diffusion/ldm3d_diffusion.md/0 | {
"file_path": "diffusers/docs/source/en/api/pipelines/stable_diffusion/ldm3d_diffusion.md",
"repo_id": "diffusers",
"token_count": 1200
} | 89 |
# ConsistencyDecoderScheduler
This scheduler is a part of the [`ConsistencyDecoderPipeline`] and was introduced in [DALL-E 3](https://openai.com/dall-e-3).
The original codebase can be found at [openai/consistency_models](https://github.com/openai/consistency_models).
## ConsistencyDecoderScheduler
[[autodoc]] sch... | diffusers/docs/source/en/api/schedulers/consistency_decoder.md/0 | {
"file_path": "diffusers/docs/source/en/api/schedulers/consistency_decoder.md",
"repo_id": "diffusers",
"token_count": 132
} | 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/index.md/0 | {
"file_path": "diffusers/docs/source/en/index.md",
"repo_id": "diffusers",
"token_count": 1317
} | 91 |
# Adapt a model to a new task
Many diffusion systems share the same components, allowing you to adapt a pretrained model for one task to an entirely different task.
This guide will show you how to adapt a pretrained text-to-image model for inpainting by initializing and modifying the architecture of a pretrained [`UN... | diffusers/docs/source/en/training/adapt_a_model.md/0 | {
"file_path": "diffusers/docs/source/en/training/adapt_a_model.md",
"repo_id": "diffusers",
"token_count": 779
} | 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/training/unconditional_training.md/0 | {
"file_path": "diffusers/docs/source/en/training/unconditional_training.md",
"repo_id": "diffusers",
"token_count": 2950
} | 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/using-diffusers/diffedit.md/0 | {
"file_path": "diffusers/docs/source/en/using-diffusers/diffedit.md",
"repo_id": "diffusers",
"token_count": 3848
} | 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/using-diffusers/reusing_seeds.md/0 | {
"file_path": "diffusers/docs/source/en/using-diffusers/reusing_seeds.md",
"repo_id": "diffusers",
"token_count": 1100
} | 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/ja/stable_diffusion.md/0 | {
"file_path": "diffusers/docs/source/ja/stable_diffusion.md",
"repo_id": "diffusers",
"token_count": 6242
} | 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/ko/optimization/torch2.0.md/0 | {
"file_path": "diffusers/docs/source/ko/optimization/torch2.0.md",
"repo_id": "diffusers",
"token_count": 10791
} | 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 agree... | diffusers/docs/source/ko/tutorials/basic_training.md/0 | {
"file_path": "diffusers/docs/source/ko/tutorials/basic_training.md",
"repo_id": "diffusers",
"token_count": 11286
} | 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/reusing_seeds.md/0 | {
"file_path": "diffusers/docs/source/ko/using-diffusers/reusing_seeds.md",
"repo_id": "diffusers",
"token_count": 1923
} | 99 |
<!--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/zh/stable_diffusion.md/0 | {
"file_path": "diffusers/docs/source/zh/stable_diffusion.md",
"repo_id": "diffusers",
"token_count": 6189
} | 100 |
import inspect
from typing import Any, Dict, List, Optional, Union
import torch
import torch.nn as nn
from transformers import AutoModel, AutoTokenizer, CLIPImageProcessor
from diffusers import DiffusionPipeline
from diffusers.image_processor import VaeImageProcessor
from diffusers.loaders import LoraLoaderMixin
from... | diffusers/examples/community/gluegen.py/0 | {
"file_path": "diffusers/examples/community/gluegen.py",
"repo_id": "diffusers",
"token_count": 17627
} | 101 |
from typing import Any, Callable, Dict, List, Optional, Union
import numpy as np
import PIL.Image
import torch
from diffusers import StableDiffusionImg2ImgPipeline
from diffusers.pipelines.stable_diffusion import StableDiffusionPipelineOutput
class MaskedStableDiffusionImg2ImgPipeline(StableDiffusionImg2ImgPipeline... | diffusers/examples/community/masked_stable_diffusion_img2img.py/0 | {
"file_path": "diffusers/examples/community/masked_stable_diffusion_img2img.py",
"repo_id": "diffusers",
"token_count": 6312
} | 102 |
# A diffuser version implementation of Zero1to3 (https://github.com/cvlab-columbia/zero123), ICCV 2023
# by Xin Kong
import inspect
from typing import Any, Callable, Dict, List, Optional, Union
import kornia
import numpy as np
import PIL.Image
import torch
from packaging import version
from transformers import CLIPFe... | diffusers/examples/community/pipeline_zero1to3.py/0 | {
"file_path": "diffusers/examples/community/pipeline_zero1to3.py",
"repo_id": "diffusers",
"token_count": 19739
} | 103 |
from typing import Any, Callable, Dict, List, Optional, Union
import PIL.Image
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusionImg... | diffusers/examples/community/stable_diffusion_mega.py/0 | {
"file_path": "diffusers/examples/community/stable_diffusion_mega.py",
"repo_id": "diffusers",
"token_count": 4380
} | 104 |
# Custom Diffusion training example
[Custom Diffusion](https://arxiv.org/abs/2212.04488) is a method to customize text-to-image models like Stable Diffusion given just a few (4~5) images of a subject.
The `train_custom_diffusion.py` script shows how to implement the training procedure and adapt it for stable diffusio... | diffusers/examples/custom_diffusion/README.md/0 | {
"file_path": "diffusers/examples/custom_diffusion/README.md",
"repo_id": "diffusers",
"token_count": 3550
} | 105 |
# Inference Examples
**The inference examples folder is deprecated and will be removed in a future version**.
**Officially supported inference examples can be found in the [Pipelines folder](https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines)**.
- For `Image-to-Image text-guided generation wit... | diffusers/examples/inference/README.md/0 | {
"file_path": "diffusers/examples/inference/README.md",
"repo_id": "diffusers",
"token_count": 252
} | 106 |
import d4rl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
config = {
"n_samples": 64,
"horizon": 32,
"num_inference_steps": 20,
"n_guide_steps": 2, # can set to 0 for faster sampling, does not use value network
"scale_grad_by_std": True,
"scale": 0.1,... | diffusers/examples/reinforcement_learning/run_diffuser_locomotion.py/0 | {
"file_path": "diffusers/examples/reinforcement_learning/run_diffuser_locomotion.py",
"repo_id": "diffusers",
"token_count": 724
} | 107 |
# 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/research_projects/controlnetxs/pipeline_controlnet_xs_sd_xl.py/0 | {
"file_path": "diffusers/examples/research_projects/controlnetxs/pipeline_controlnet_xs_sd_xl.py",
"repo_id": "diffusers",
"token_count": 24961
} | 108 |
# Distillation for quantization on Textual Inversion models to personalize text2image
[Textual inversion](https://arxiv.org/abs/2208.01618) is a method to personalize text2image models like stable diffusion on your own images._By using just 3-5 images new concepts can be taught to Stable Diffusion and the model person... | diffusers/examples/research_projects/intel_opts/textual_inversion_dfq/README.md/0 | {
"file_path": "diffusers/examples/research_projects/intel_opts/textual_inversion_dfq/README.md",
"repo_id": "diffusers",
"token_count": 1443
} | 109 |
# RealFill
[RealFill](https://arxiv.org/abs/2309.16668) is a method to personalize text2image inpainting models like stable diffusion inpainting given just a few(1~5) images of a scene.
The `train_realfill.py` script shows how to implement the training procedure for stable diffusion inpainting.
## Running locally wi... | diffusers/examples/research_projects/realfill/README.md/0 | {
"file_path": "diffusers/examples/research_projects/realfill/README.md",
"repo_id": "diffusers",
"token_count": 1321
} | 110 |
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 PIL
import torch
import torch.utils.checkpoint
import transformers
from flax import jax_utils
from flax.training import train_state
from flax.training.co... | diffusers/examples/textual_inversion/textual_inversion_flax.py/0 | {
"file_path": "diffusers/examples/textual_inversion/textual_inversion_flax.py",
"repo_id": "diffusers",
"token_count": 11076
} | 111 |
import inspect
import os
from argparse import ArgumentParser
import numpy as np
import torch
from muse import MaskGiTUViT, VQGANModel
from muse import PipelineMuse as OldPipelineMuse
from transformers import CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import VQModel
from diffusers.models.attention_proce... | diffusers/scripts/convert_amused.py/0 | {
"file_path": "diffusers/scripts/convert_amused.py",
"repo_id": "diffusers",
"token_count": 12883
} | 112 |
import argparse
import huggingface_hub
import k_diffusion as K
import torch
from diffusers import UNet2DConditionModel
UPSCALER_REPO = "pcuenq/k-upscaler"
def resnet_to_diffusers_checkpoint(resnet, checkpoint, *, diffusers_resnet_prefix, resnet_prefix):
rv = {
# norm1
f"{diffusers_resnet_prefi... | diffusers/scripts/convert_k_upscaler_to_diffusers.py/0 | {
"file_path": "diffusers/scripts/convert_k_upscaler_to_diffusers.py",
"repo_id": "diffusers",
"token_count": 5645
} | 113 |
import argparse
import os
import torch
from transformers import T5EncoderModel, T5Tokenizer
from diffusers import AutoencoderKL, DPMSolverMultistepScheduler, PixArtAlphaPipeline, Transformer2DModel
ckpt_id = "PixArt-alpha/PixArt-alpha"
# https://github.com/PixArt-alpha/PixArt-alpha/blob/0f55e922376d8b797edd44d25d0e... | diffusers/scripts/convert_pixart_alpha_to_diffusers.py/0 | {
"file_path": "diffusers/scripts/convert_pixart_alpha_to_diffusers.py",
"repo_id": "diffusers",
"token_count": 4086
} | 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/setup.py/0 | {
"file_path": "diffusers/setup.py",
"repo_id": "diffusers",
"token_count": 3776
} | 115 |
# 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/controlnet.py/0 | {
"file_path": "diffusers/src/diffusers/loaders/controlnet.py",
"repo_id": "diffusers",
"token_count": 2757
} | 116 |
# 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/attention_processor.py/0 | {
"file_path": "diffusers/src/diffusers/models/attention_processor.py",
"repo_id": "diffusers",
"token_count": 46582
} | 117 |
# 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/src/diffusers/models/modeling_flax_utils.py/0 | {
"file_path": "diffusers/src/diffusers/models/modeling_flax_utils.py",
"repo_id": "diffusers",
"token_count": 11976
} | 118 |
# 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/transformers/transformer_temporal.py/0 | {
"file_path": "diffusers/src/diffusers/models/transformers/transformer_temporal.py",
"repo_id": "diffusers",
"token_count": 7287
} | 119 |
# Copyright 2023 Alibaba DAMO-VILAB 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
#
# Unles... | diffusers/src/diffusers/models/unets/unet_i2vgen_xl.py/0 | {
"file_path": "diffusers/src/diffusers/models/unets/unet_i2vgen_xl.py",
"repo_id": "diffusers",
"token_count": 13603
} | 120 |
# 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/animatediff/pipeline_animatediff.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/animatediff/pipeline_animatediff.py",
"repo_id": "diffusers",
"token_count": 22983
} | 121 |
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
} | 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 = {
"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
} | 123 |
# Copyright 2022 The Music Spectrogram Diffusion Authors.
# 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... | 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": 1255
} | 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/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": 9852
} | 125 |
# 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/kandinsky2_2/pipeline_kandinsky2_2_combined.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/kandinsky2_2/pipeline_kandinsky2_2_combined.py",
"repo_id": "diffusers",
"token_count": 18701
} | 126 |
import inspect
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL.Image
import torch
import torch.utils.checkpoint
from ...models import UNet2DModel, VQModel
from ...schedulers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscret... | diffusers/src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion_superresolution.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion_superresolution.py",
"repo_id": "diffusers",
"token_count": 3451
} | 127 |
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/shap_e/__init__.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/shap_e/__init__.py",
"repo_id": "diffusers",
"token_count": 939
} | 128 |
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...utils import BaseOutput, is_flax_available
@dataclass
class StableDiffusionPipelineOutput(BaseOutput):
"""
Output class for Stable Diffusion pipelines.
Args:
images (`List[PIL.... | diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_output.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_output.py",
"repo_id": "diffusers",
"token_count": 598
} | 129 |
from dataclasses import dataclass
from typing import List, Union
import numpy as np
import torch
from ...utils import (
BaseOutput,
)
@dataclass
class TextToVideoSDPipelineOutput(BaseOutput):
"""
Output class for text-to-video pipelines.
Args:
frames (`List[np.ndarray]` or `torch.FloatTenso... | diffusers/src/diffusers/pipelines/text_to_video_synthesis/pipeline_output.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/text_to_video_synthesis/pipeline_output.py",
"repo_id": "diffusers",
"token_count": 221
} | 130 |
# Copyright (c) 2023 Dominic Rampas MIT License
# 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/licen... | diffusers/src/diffusers/pipelines/wuerstchen/modeling_wuerstchen_diffnext.py/0 | {
"file_path": "diffusers/src/diffusers/pipelines/wuerstchen/modeling_wuerstchen_diffnext.py",
"repo_id": "diffusers",
"token_count": 5545
} | 131 |
# 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/schedulers/scheduling_ddim_inverse.py/0 | {
"file_path": "diffusers/src/diffusers/schedulers/scheduling_ddim_inverse.py",
"repo_id": "diffusers",
"token_count": 7389
} | 132 |
# Copyright 2023 Zhejiang University Team and The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
#... | diffusers/src/diffusers/schedulers/scheduling_ipndm.py/0 | {
"file_path": "diffusers/src/diffusers/schedulers/scheduling_ipndm.py",
"repo_id": "diffusers",
"token_count": 3645
} | 133 |
# 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/schedulers/scheduling_utils_flax.py/0 | {
"file_path": "diffusers/src/diffusers/schedulers/scheduling_utils_flax.py",
"repo_id": "diffusers",
"token_count": 5031
} | 134 |
# This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends
class StableDiffusionKDiffusionPipeline(metaclass=DummyObject):
_backends = ["torch", "transformers", "k_diffusion"]
def __init__(self, *args, **kwargs):
requires_backends(se... | diffusers/src/diffusers/utils/dummy_torch_and_transformers_and_k_diffusion_objects.py/0 | {
"file_path": "diffusers/src/diffusers/utils/dummy_torch_and_transformers_and_k_diffusion_objects.py",
"repo_id": "diffusers",
"token_count": 451
} | 135 |
# Copyright 2020 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | diffusers/src/diffusers/utils/versions.py/0 | {
"file_path": "diffusers/src/diffusers/utils/versions.py",
"repo_id": "diffusers",
"token_count": 1699
} | 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/models/test_layers_utils.py/0 | {
"file_path": "diffusers/tests/models/test_layers_utils.py",
"repo_id": "diffusers",
"token_count": 10696
} | 137 |
# 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/tests/others/test_check_dummies.py/0 | {
"file_path": "diffusers/tests/others/test_check_dummies.py",
"repo_id": "diffusers",
"token_count": 1873
} | 138 |
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AnimateDiffVideoToVideoPipeline,
AutoencoderKL,
DDIMScheduler,
MotionAdapter,
UNet2DConditionModel,
UNetMotionMod... | diffusers/tests/pipelines/animatediff/test_animatediff_video2video.py/0 | {
"file_path": "diffusers/tests/pipelines/animatediff/test_animatediff_video2video.py",
"repo_id": "diffusers",
"token_count": 4546
} | 139 |
# 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/controlnet/test_controlnet_sdxl_img2img.py/0 | {
"file_path": "diffusers/tests/pipelines/controlnet/test_controlnet_sdxl_img2img.py",
"repo_id": "diffusers",
"token_count": 5979
} | 140 |
# 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/dit/test_dit.py/0 | {
"file_path": "diffusers/tests/pipelines/dit/test_dit.py",
"repo_id": "diffusers",
"token_count": 2339
} | 141 |
# 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/kandinsky2_2/test_kandinsky_inpaint.py/0 | {
"file_path": "diffusers/tests/pipelines/kandinsky2_2/test_kandinsky_inpaint.py",
"repo_id": "diffusers",
"token_count": 5423
} | 142 |
# coding=utf-8
# Copyright 2022 HuggingFace Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or ag... | diffusers/tests/pipelines/stable_diffusion/test_onnx_stable_diffusion_upscale.py/0 | {
"file_path": "diffusers/tests/pipelines/stable_diffusion/test_onnx_stable_diffusion_upscale.py",
"repo_id": "diffusers",
"token_count": 3918
} | 143 |
# 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/test_pipelines_auto.py/0 | {
"file_path": "diffusers/tests/pipelines/test_pipelines_auto.py",
"repo_id": "diffusers",
"token_count": 6542
} | 144 |
# 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/wuerstchen/test_wuerstchen_combined.py/0 | {
"file_path": "diffusers/tests/pipelines/wuerstchen/test_wuerstchen_combined.py",
"repo_id": "diffusers",
"token_count": 3552
} | 145 |
import torch
from diffusers import EulerAncestralDiscreteScheduler
from diffusers.utils.testing_utils import torch_device
from .test_schedulers import SchedulerCommonTest
class EulerAncestralDiscreteSchedulerTest(SchedulerCommonTest):
scheduler_classes = (EulerAncestralDiscreteScheduler,)
num_inference_step... | diffusers/tests/schedulers/test_scheduler_euler_ancestral.py/0 | {
"file_path": "diffusers/tests/schedulers/test_scheduler_euler_ancestral.py",
"repo_id": "diffusers",
"token_count": 2492
} | 146 |
# 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_copies.py/0 | {
"file_path": "diffusers/utils/check_copies.py",
"repo_id": "diffusers",
"token_count": 3398
} | 147 |
<jupyter_start><jupyter_text>DDIM InversionIn this notebook we will explore **inversion**, see how it relates to sampling, and apply it to the task of editing images with Stable Diffusion. What You Will Learn- How DDIM sampling works- Deterministic vs Stochastic samplers- The theory behind DDIM inversion- Editing imag... | diffusion-models-class/units/en/unit4/ddim_inversion.ipynb/0 | {
"file_path": "diffusion-models-class/units/en/unit4/ddim_inversion.ipynb",
"repo_id": "diffusion-models-class",
"token_count": 5328
} | 148 |
# Modèle de diffusion conditionné par la classe
<CourseFloatingBanner unit={2}
classNames="absolute z-10 right-0 top-0"
notebooks={[
{label: "Modèle de diffusion conditionné par la classe", value: "https://colab.research.google.com/github/huggingface/diffusion-models-class/blob/main/units/fr/unit3/class_condition... | diffusion-models-class/units/fr/unit2/3.mdx/0 | {
"file_path": "diffusion-models-class/units/fr/unit2/3.mdx",
"repo_id": "diffusion-models-class",
"token_count": 4505
} | 149 |
# Débruitage inverse des modèles de diffusion implicites (DDIM)
<CourseFloatingBanner unit={4}
classNames="absolute z-10 right-0 top-0"
notebooks={[
{label: "Débruitage inverse des modèles de diffusion implicites (DDIM)", value: "https://colab.research.google.com/github/huggingface/diffusion-models-class/blob/mai... | diffusion-models-class/units/fr/unit4/2.mdx/0 | {
"file_path": "diffusion-models-class/units/fr/unit4/2.mdx",
"repo_id": "diffusion-models-class",
"token_count": 9611
} | 150 |
.PHONY: doc-notebooks
doc-notebooks:
python utils/convert_doc_to_notebooks.py
| notebooks/Makefile/0 | {
"file_path": "notebooks/Makefile",
"repo_id": "notebooks",
"token_count": 33
} | 151 |
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