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# 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
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import re import textwrap from collections import Counter from itertools import groupby from operator import itemgetter from typing import Any, ClassVar, Dict, List, Optional, Tuple import yaml from huggingface_hub import DatasetCardData from ..config import METADATA_CONFIGS_FIELD from ..features import Features from...
datasets/src/datasets/utils/metadata.py/0
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--- TODO: "Add YAML tags here. Delete these instructions and copy-paste the YAML tags obtained with the online tagging app: https://huggingface.co/spaces/huggingface/datasets-tagging" --- # Dataset Card for [Dataset Name] ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-...
datasets/templates/README.md/0
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from unittest.mock import patch import pyspark import pytest from datasets.builder import InvalidConfigName from datasets.data_files import DataFilesList from datasets.packaged_modules.spark.spark import ( Spark, SparkConfig, SparkExamplesIterable, _generate_iterable_examples, ) from ..utils import (...
datasets/tests/packaged_modules/test_spark.py/0
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import os import re from pathlib import Path from unittest.mock import patch import pytest import zstandard as zstd from fsspec.registry import _registry as _fsspec_registry from fsspec.spec import AbstractBufferedFile, AbstractFileSystem from huggingface_hub.errors import OfflineModeIsEnabled from datasets.download....
datasets/tests/test_file_utils.py/0
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import os import tempfile from functools import partial from unittest import TestCase from unittest.mock import patch import numpy as np import pytest from datasets.arrow_dataset import Dataset from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex from .utils import require_elasticsearch, require_...
datasets/tests/test_search.py/0
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import os import sys import torch from diffusers import ( AutoPipelineForImage2Image, AutoPipelineForInpainting, AutoPipelineForText2Image, ControlNetModel, LCMScheduler, StableDiffusionAdapterPipeline, StableDiffusionControlNetPipeline, StableDiffusionXLAdapterPipeline, StableDiff...
diffusers/benchmarks/base_classes.py/0
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<!--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/ip_adapter.md/0
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<!-- Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agree...
diffusers/docs/source/en/api/models/autoencoderkl_allegro.md/0
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<!-- 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 applic...
diffusers/docs/source/en/api/pipelines/ltx_video.md/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to...
diffusers/docs/source/en/api/pipelines/shap_e.md/0
{ "file_path": "diffusers/docs/source/en/api/pipelines/shap_e.md", "repo_id": "diffusers", "token_count": 590 }
<!--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/schedulers/ddim.md/0
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<!--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/schedulers/lms_discrete.md/0
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<!--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/open_vino.md/0
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# Create a dataset for training There are many datasets on the [Hub](https://huggingface.co/datasets?task_categories=task_categories:text-to-image&sort=downloads) to train a model on, but if you can't find one you're interested in or want to use your own, you can create a dataset with the 🤗 [Datasets](https://hugging...
diffusers/docs/source/en/training/create_dataset.md/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
diffusers/docs/source/en/tutorials/autopipeline.md/0
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<!--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/image_quality.md/0
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<!--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/scheduler_features.md/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
diffusers/docs/source/ja/quicktour.md/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
diffusers/docs/source/ko/optimization/mps.md/0
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<!--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/other-formats.md/0
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# LoRA finetuning example for CogVideoX Low-Rank Adaption of Large Language Models was first introduced by Microsoft in [LoRA: Low-Rank Adaptation of Large Language Models](https://arxiv.org/abs/2106.09685) by *Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen*. ...
diffusers/examples/cogvideo/README.md/0
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# 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/examples/community/fresco_v2v.py/0
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## ---------------------------------------------------------- # A SDXL pipeline can take unlimited weighted prompt # # Author: Andrew Zhu # GitHub: https://github.com/xhinker # Medium: https://medium.com/@xhinker ## ----------------------------------------------------------- import inspect import os from typing import...
diffusers/examples/community/lpw_stable_diffusion_xl.py/0
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# Copyright 2024 The InstantX 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 l...
diffusers/examples/community/pipeline_stable_diffusion_xl_instandid_img2img.py/0
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import inspect import os import random import re from dataclasses import dataclass from typing import Callable, Dict, List, Optional, Union import torch from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer from diffusers.configuration_utils import FrozenDict from diffusers.models import Autoencod...
diffusers/examples/community/wildcard_stable_diffusion.py/0
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# DreamBooth training example for FLUX.1 [dev] [DreamBooth](https://arxiv.org/abs/2208.12242) is a method to personalize text2image models like stable diffusion given just a few (3~5) images of a subject. The `train_dreambooth_flux.py` script shows how to implement the training procedure and adapt it for [FLUX.1 [dev...
diffusers/examples/dreambooth/README_flux.md/0
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# coding=utf-8 # Copyright 2025 suzukimain # # 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 t...
diffusers/examples/model_search/pipeline_easy.py/0
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compute_environment: LOCAL_MACHINE debug: false deepspeed_config: gradient_accumulation_steps: 1 gradient_clipping: 1.0 offload_optimizer_device: cpu offload_param_device: cpu zero3_init_flag: false zero_stage: 2 distributed_type: DEEPSPEED downcast_bf16: 'no' enable_cpu_affinity: false machine_rank: 0 main...
diffusers/examples/research_projects/flux_lora_quantization/ds2.yaml/0
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# Generating images using Flux and PyTorch/XLA The `flux_inference` script shows how to do image generation using Flux on TPU devices using PyTorch/XLA. It uses the pallas kernel for flash attention for faster generation. It has been tested on [Trillium](https://cloud.google.com/blog/products/compute/introducing-tril...
diffusers/examples/research_projects/pytorch_xla/inference/flux/README.md/0
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#!/usr/bin/env python # coding=utf-8 # Copyright 2025 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/research_projects/scheduled_huber_loss_training/text_to_image/train_text_to_image.py/0
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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
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import argparse import os import torch from huggingface_hub import create_repo, upload_folder from safetensors.torch import load_file, save_file def convert_motion_module(original_state_dict): converted_state_dict = {} for k, v in original_state_dict.items(): if "pos_encoder" in k: contin...
diffusers/scripts/convert_animatediff_motion_lora_to_diffusers.py/0
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import argparse import os import torch from torchvision.datasets.utils import download_url from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, Transformer2DModel pretrained_models = {512: "DiT-XL-2-512x512.pt", 256: "DiT-XL-2-256x256.pt"} def download_model(model_name): """ Downloads a pre-tr...
diffusers/scripts/convert_dit_to_diffusers.py/0
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import argparse import os import torch from safetensors.torch import load_file from transformers import AutoModel, AutoTokenizer from diffusers import AutoencoderKL, FlowMatchEulerDiscreteScheduler, LuminaNextDiT2DModel, LuminaText2ImgPipeline def main(args): # checkpoint from https://huggingface.co/Alpha-VLLM/...
diffusers/scripts/convert_lumina_to_diffusers.py/0
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import argparse from contextlib import nullcontext import safetensors.torch import torch from accelerate import init_empty_weights from diffusers import AutoencoderKL, SD3Transformer2DModel from diffusers.loaders.single_file_utils import convert_ldm_vae_checkpoint from diffusers.models.modeling_utils import load_mode...
diffusers/scripts/convert_sd3_to_diffusers.py/0
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# Run inside root directory of official source code: https://github.com/dome272/wuerstchen/ import os import torch from transformers import AutoTokenizer, CLIPTextModel from vqgan import VQModel from diffusers import ( DDPMWuerstchenScheduler, WuerstchenCombinedPipeline, WuerstchenDecoderPipeline, Wue...
diffusers/scripts/convert_wuerstchen.py/0
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# 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/textual_inversion.py/0
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# Copyright 2024 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
diffusers/src/diffusers/models/autoencoders/autoencoder_kl.py/0
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# 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/controlnet_sparsectrl.py/0
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# coding=utf-8 # Copyright 2025 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_pytorch_utils.py/0
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# Copyright 2024 Alpha-VLLM 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 # # Unles...
diffusers/src/diffusers/models/transformers/lumina_nextdit2d.py/0
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# 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_1d.py/0
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# 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/vae_flax.py/0
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# Copyright 2024 Salesforce.com, inc. # Copyright 2024 The HuggingFace Team. All rights reserved.# # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE...
diffusers/src/diffusers/pipelines/blip_diffusion/pipeline_blip_diffusion.py/0
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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
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from typing import TYPE_CHECKING from ....utils import DIFFUSERS_SLOW_IMPORT, _LazyModule _import_structure = {"pipeline_latent_diffusion_uncond": ["LDMPipeline"]} if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT: from .pipeline_latent_diffusion_uncond import LDMPipeline else: import sys sys.modules[__name__]...
diffusers/src/diffusers/pipelines/deprecated/latent_diffusion_uncond/__init__.py/0
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# 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/stable_diffusion_variants/pipeline_stable_diffusion_inpaint_legacy.py/0
{ "file_path": "diffusers/src/diffusers/pipelines/deprecated/stable_diffusion_variants/pipeline_stable_diffusion_inpaint_legacy.py", "repo_id": "diffusers", "token_count": 18223 }
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 = {} _additional_imports = {} _import_structure = {"pipeline_output": ["FluxPipe...
diffusers/src/diffusers/pipelines/flux/__init__.py/0
{ "file_path": "diffusers/src/diffusers/pipelines/flux/__init__.py", "repo_id": "diffusers", "token_count": 1276 }
# 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_combined.py/0
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# Copyright 2024 ChatGLM3-6B Model Team, Kwai-Kolors 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...
diffusers/src/diffusers/pipelines/kolors/tokenizer.py/0
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from dataclasses import dataclass import torch from diffusers.utils import BaseOutput @dataclass class LTXPipelineOutput(BaseOutput): r""" Output class for LTX pipelines. Args: frames (`torch.Tensor`, `np.ndarray`, or List[List[PIL.Image.Image]]): List of video outputs - It can be a...
diffusers/src/diffusers/pipelines/ltx/pipeline_output.py/0
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from dataclasses import dataclass from typing import TYPE_CHECKING, List, Optional, Union import numpy as np import PIL from PIL import Image from ...utils import ( DIFFUSERS_SLOW_IMPORT, OptionalDependencyNotAvailable, _LazyModule, get_objects_from_module, is_torch_available, is_transformers_...
diffusers/src/diffusers/pipelines/paint_by_example/__init__.py/0
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import inspect from itertools import repeat from typing import Callable, List, Optional, Union import torch from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer from ...image_processor import VaeImageProcessor from ...models import AutoencoderKL, UNet2DConditionModel from ...pipelines.stable_diff...
diffusers/src/diffusers/pipelines/semantic_stable_diffusion/pipeline_semantic_stable_diffusion.py/0
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# 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_xl/pipeline_flax_stable_diffusion_xl.py/0
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import copy import inspect from dataclasses import dataclass from typing import Callable, List, Optional, Union import numpy as np import PIL.Image import torch import torch.nn.functional as F from torch.nn.functional import grid_sample from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer from .....
diffusers/src/diffusers/pipelines/text_to_video_synthesis/pipeline_text_to_video_zero.py/0
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# 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/wuerstchen/pipeline_wuerstchen.py/0
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# Copyright 2024 ParaDiGMS 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 # # Unless...
diffusers/src/diffusers/schedulers/scheduling_ddpm_parallel.py/0
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# This file is autogenerated by the command `make fix-copies`, do not edit. from ..utils import DummyObject, requires_backends class LMSDiscreteScheduler(metaclass=DummyObject): _backends = ["torch", "scipy"] def __init__(self, *args, **kwargs): requires_backends(self, ["torch", "scipy"]) @class...
diffusers/src/diffusers/utils/dummy_torch_and_scipy_objects.py/0
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from typing import List import PIL.Image import PIL.ImageOps from packaging import version from PIL import Image if version.parse(version.parse(PIL.__version__).base_version) >= version.parse("9.1.0"): PIL_INTERPOLATION = { "linear": PIL.Image.Resampling.BILINEAR, "bilinear": PIL.Image.Resampling...
diffusers/src/diffusers/utils/pil_utils.py/0
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# 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 agreed to in writ...
diffusers/tests/lora/test_lora_layers_ltx_video.py/0
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# coding=utf-8 # Copyright 2024 HuggingFace Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or ag...
diffusers/tests/models/autoencoders/test_models_autoencoder_oobleck.py/0
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# coding=utf-8 # Copyright 2024 HuggingFace Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or ag...
diffusers/tests/models/transformers/test_models_transformer_aura_flow.py/0
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# coding=utf-8 # Copyright 2024 HuggingFace Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or ag...
diffusers/tests/models/unets/test_models_unet_2d.py/0
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import pickle as pkl import unittest from dataclasses import dataclass from typing import List, Union import numpy as np import PIL.Image from diffusers.utils.outputs import BaseOutput from diffusers.utils.testing_utils import require_torch @dataclass class CustomOutput(BaseOutput): images: Union[List[PIL.Image...
diffusers/tests/others/test_outputs.py/0
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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, DPMSolverMultistepScheduler, LCMScheduler, MotionA...
diffusers/tests/pipelines/animatediff/test_animatediff_video2video.py/0
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# Copyright 2024 The HuggingFace Team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in...
diffusers/tests/pipelines/cogview3/test_cogview3plus.py/0
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import unittest import numpy as np import torch from transformers import AutoTokenizer, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, T5EncoderModel from diffusers import ( AutoencoderKL, FlowMatchEulerDiscreteScheduler, FluxControlNetImg2ImgPipeline, FluxControlNetModel, FluxTransformer2DModel, )...
diffusers/tests/pipelines/controlnet_flux/test_controlnet_flux_img2img.py/0
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import tempfile import numpy as np import torch from transformers import AutoTokenizer, T5EncoderModel from diffusers import DDPMScheduler, UNet2DConditionModel from diffusers.models.attention_processor import AttnAddedKVProcessor from diffusers.pipelines.deepfloyd_if import IFWatermarker from diffusers.utils.testing...
diffusers/tests/pipelines/deepfloyd_if/__init__.py/0
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# 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.py/0
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import inspect import unittest import numpy as np import torch from transformers import AutoTokenizer, CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer, T5EncoderModel from diffusers import ( AutoencoderKL, FlowMatchEulerDiscreteScheduler, SD3Transformer2DModel, StableDiffusion3PAGPipeline, ...
diffusers/tests/pipelines/pag/test_pag_sd3.py/0
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# coding=utf-8 # Copyright 2024 HuggingFace Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or ag...
diffusers/tests/pipelines/stable_diffusion/test_onnx_stable_diffusion.py/0
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# 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_latent_upscale.py/0
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# 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/tests/quantization/torchao/test_torchao.py/0
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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
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# 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/notify_benchmarking_status.py/0
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This tutorial explains how to use [Moss v1](https://github.com/jess-moss/moss-robot-arms) with LeRobot. ## Source the parts Follow this [README](https://github.com/jess-moss/moss-robot-arms). It contains the bill of materials, with link to source the parts, as well as the instructions to 3D print the parts, and advic...
lerobot/examples/11_use_moss.md/0
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#!/usr/bin/env python # 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 # # ...
lerobot/lerobot/common/datasets/factory.py/0
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#!/usr/bin/env python # 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 # # ...
lerobot/lerobot/common/datasets/push_dataset_to_hub/_encode_datasets.py/0
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from dataclasses import dataclass, field from lerobot.common.optim.optimizers import AdamWConfig from lerobot.common.optim.schedulers import ( CosineDecayWithWarmupSchedulerConfig, ) from lerobot.configs.policies import PreTrainedConfig from lerobot.configs.types import FeatureType, NormalizationMode, PolicyFeatur...
lerobot/lerobot/common/policies/pi0/configuration_pi0.py/0
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""" This file contains utilities for recording frames from Intel Realsense cameras. """ import argparse import concurrent.futures import logging import math import shutil import threading import time import traceback from collections import Counter from pathlib import Path from threading import Thread import numpy as...
lerobot/lerobot/common/robot_devices/cameras/intelrealsense.py/0
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#!/usr/bin/env python # 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 # # ...
lerobot/lerobot/common/utils/benchmark.py/0
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import os import time from pathlib import Path from serial.tools import list_ports # Part of pyserial library def find_available_ports(): if os.name == "nt": # Windows # List COM ports using pyserial ports = [port.device for port in list_ports.comports()] else: # Linux/macOS # List...
lerobot/lerobot/scripts/find_motors_bus_port.py/0
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#!/usr/bin/env python # 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 # # ...
lerobot/tests/lerobot/common/datasets/test_utils.py/0
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import queue import time from multiprocessing import queues from unittest.mock import MagicMock, patch import numpy as np import pytest from PIL import Image from lerobot.common.datasets.image_writer import ( AsyncImageWriter, image_array_to_image, safe_stop_image_writer, write_image, ) DUMMY_IMAGE =...
lerobot/tests/test_image_writer.py/0
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# Model arguments model_name_or_path: Qwen/Qwen2.5-Math-7B model_revision: main torch_dtype: bfloat16 attn_implementation: flash_attention_2 # Data training arguments dataset_name: DigitalLearningGmbH/MATH-lighteval dataset_configs: - train # Num processes is less by 1 as vLLM is using 1 GPU num_processes: 7 # GRPO t...
open-r1/recipes/Qwen2.5-Math-7B/grpo/config_simple_rl.yaml/0
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"""Reward functions for GRPO training.""" import math import re from latex2sympy2_extended import NormalizationConfig from math_verify import LatexExtractionConfig, parse, verify def accuracy_reward(completions, solution, **kwargs): """Reward function that checks if the completion is the same as the ground trut...
open-r1/src/open_r1/rewards.py/0
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# Minimal makefile for Sphinx documentation # # You can set these variables from the command line. SPHINXOPTS = SPHINXBUILD = sphinx-build SOURCEDIR = source BUILDDIR = _build # Put it first so that "make" without argument is like "make help". help: @$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" ...
peft/docs/Makefile/0
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<!--Copyright 2024 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
peft/docs/source/developer_guides/model_merging.md/0
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<!--Copyright 2023 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
peft/docs/source/package_reference/tuners.md/0
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IDX=$1 PROMPT_IDX=$((IDX % 25)) CLASS_IDX=$((IDX % 30)) # Define the UNIQUE_TOKEN, CLASS_TOKENs, and SUBJECT_NAMES UNIQUE_TOKEN="qwe" SUBJECT_NAMES=( "backpack" "backpack_dog" "bear_plushie" "berry_bowl" "can" "candle" "cat" "cat2" "clock" "colorful_sneaker" "dog" "dog2" "dog3" "dog5" "dog6" "dog7" "d...
peft/examples/boft_dreambooth/train_dreambooth.sh/0
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<jupyter_start><jupyter_code>from datasets import load_dataset from transformers import set_seed, AutoModelForSeq2SeqLM, AutoTokenizer from peft import get_peft_model, MultitaskPromptTuningConfig, TaskType, MultitaskPromptTuningInit set_seed(42) model_name = "google/flan-t5-base" peft_config = MultitaskPromptTuningC...
peft/examples/conditional_generation/multitask_prompt_tuning.ipynb/0
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<jupyter_start><jupyter_text>CPT Training and InferenceThis notebook demonstrates the training and evaluation process of Context-Aware Prompt Tuning (CPT) using the Hugging Face Trainer. For more details, refer to the [Paper](https://huggingface.co/papers/2410.17222). Sections Overview:1. **Setup**: Import libraries an...
peft/examples/cpt_finetuning/cpt_train_and_inference.ipynb/0
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<jupyter_start><jupyter_text>Finetuning Whisper-large-V2 on Colab using PEFT-Lora + BNB INT8 training In this Colab, we present a step-by-step guide on how to fine-tune Whisper for any multilingual ASR dataset using Hugging Face 🤗 Transformers and 🤗 PEFT. Using 🤗 PEFT and `bitsandbytes`, you can train the `whisper-l...
peft/examples/int8_training/peft_bnb_whisper_large_v2_training.ipynb/0
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<jupyter_start><jupyter_text>Using PEFT with custom models `peft` allows us to fine-tune models efficiently with LoRA. In this short notebook, we will demonstrate how to train a simple multilayer perceptron (MLP) using `peft`. Imports Make sure that you have the latest version of `peft` installed. To ensure that, run ...
peft/examples/multilayer_perceptron/multilayer_perceptron_lora.ipynb/0
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accelerate launch --config_file "configs/fsdp_config.yaml" train.py \ --seed 100 \ --model_name_or_path "meta-llama/Llama-2-70b-hf" \ --dataset_name "smangrul/ultrachat-10k-chatml" \ --chat_template_format "chatml" \ --add_special_tokens False \ --append_concat_token False \ --splits "train,test" \ --max_seq_len 2048 ...
peft/examples/sft/run_peft_fsdp.sh/0
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""" Utility to clean cache files that exceed a specific time in days according to their last access time recorded in the cache. Exit code: - 1 if no candidates are found - 0 if candidates are found Deletion can be enabled by passing `-d` parameter, otherwise it will only list the candidates. """ import sys from date...
peft/scripts/ci_clean_cache.py/0
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# Copyright 2023-present the HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or...
peft/src/peft/tuners/loha/model.py/0
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# Copyright 2023-present the HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or...
peft/src/peft/tuners/lora/layer.py/0
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# Copyright 2023-present the HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or...
peft/src/peft/tuners/p_tuning/model.py/0
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