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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/fp16.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/training/ddpo.md/0
{ "file_path": "diffusers/docs/source/en/training/ddpo.md", "repo_id": "diffusers", "token_count": 321 }
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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/fast_diffusion.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/inference_with_lcm.md/0
{ "file_path": "diffusers/docs/source/en/using-diffusers/inference_with_lcm.md", "repo_id": "diffusers", "token_count": 3677 }
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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/schedulers.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/stable_diffusion.md/0
{ "file_path": "diffusers/docs/source/ja/stable_diffusion.md", "repo_id": "diffusers", "token_count": 6241 }
105
<!--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/torch2.0.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/ko/tutorials/basic_training.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/reusing_seeds.md/0
{ "file_path": "diffusers/docs/source/ko/using-diffusers/reusing_seeds.md", "repo_id": "diffusers", "token_count": 1922 }
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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/zh/stable_diffusion.md/0
{ "file_path": "diffusers/docs/source/zh/stable_diffusion.md", "repo_id": "diffusers", "token_count": 6188 }
109
# 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/dps_pipeline.py/0
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from typing import Union import torch from PIL import Image from torchvision import transforms as tfms from tqdm.auto import tqdm from transformers import CLIPTextModel, CLIPTokenizer from diffusers import ( AutoencoderKL, DDIMScheduler, DiffusionPipeline, LMSDiscreteScheduler, PNDMScheduler, ...
diffusers/examples/community/magic_mix.py/0
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# Copyright 2024 Jake Babbidge, TencentARC and The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # ...
diffusers/examples/community/pipeline_stable_diffusion_xl_controlnet_adapter_inpaint.py/0
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# Inspired by: https://github.com/haofanwang/ControlNet-for-Diffusers/ import inspect from typing import Any, Callable, Dict, List, Optional, Union import numpy as np import PIL.Image import torch import torch.nn.functional as F from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer from diffusers...
diffusers/examples/community/stable_diffusion_controlnet_inpaint_img2img.py/0
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#!/usr/bin/env python # coding=utf-8 # Copyright 2024 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LI...
diffusers/examples/controlnet/train_controlnet.py/0
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#!/usr/bin/env python # coding=utf-8 # Copyright 2024 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LI...
diffusers/examples/dreambooth/train_dreambooth.py/0
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# coding=utf-8 # Copyright 2024 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
diffusers/examples/kandinsky2_2/text_to_image/train_text_to_image_lora_decoder.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/examples/research_projects/controlnetxs/controlnetxs.py/0
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import argparse import intel_extension_for_pytorch as ipex import torch from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline parser = argparse.ArgumentParser("Stable Diffusion script with intel optimization", add_help=False) parser.add_argument("--dpm", action="store_true", help="Enable DPMSol...
diffusers/examples/research_projects/intel_opts/inference_bf16.py/0
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import argparse import copy import itertools import logging import math import os import random from pathlib import Path import numpy as np import torch import torch.nn.functional as F import torch.utils.checkpoint from accelerate import Accelerator from accelerate.logging import get_logger from accelerate.utils impor...
diffusers/examples/research_projects/multi_subject_dreambooth_inpainting/train_multi_subject_dreambooth_inpainting.py/0
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import argparse import inspect import logging import math import os from pathlib import Path import accelerate import datasets import torch import torch.nn.functional as F from accelerate import Accelerator from accelerate.logging import get_logger from accelerate.utils import ProjectConfiguration from datasets import...
diffusers/examples/research_projects/onnxruntime/unconditional_image_generation/train_unconditional.py/0
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# T2I-Adapter training example for Stable Diffusion XL (SDXL) The `train_t2i_adapter_sdxl.py` script shows how to implement the [T2I-Adapter training procedure](https://hf.co/papers/2302.08453) for [Stable Diffusion XL](https://huggingface.co/papers/2307.01952). ## Running locally with PyTorch ### Installing the dep...
diffusers/examples/t2i_adapter/README_sdxl.md/0
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#!/usr/bin/env python # coding=utf-8 # Copyright 2024 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LI...
diffusers/examples/text_to_image/train_text_to_image_sdxl.py/0
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import torch.nn as nn from torchvision.models import efficientnet_v2_l, efficientnet_v2_s from diffusers.configuration_utils import ConfigMixin, register_to_config from diffusers.models.modeling_utils import ModelMixin class EfficientNetEncoder(ModelMixin, ConfigMixin): @register_to_config def __init__(self,...
diffusers/examples/wuerstchen/text_to_image/modeling_efficient_net_encoder.py/0
{ "file_path": "diffusers/examples/wuerstchen/text_to_image/modeling_efficient_net_encoder.py", "repo_id": "diffusers", "token_count": 374 }
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import argparse import json import torch from diffusers import AutoencoderKL, DDPMPipeline, DDPMScheduler, UNet2DModel, VQModel def shave_segments(path, n_shave_prefix_segments=1): """ Removes segments. Positive values shave the first segments, negative shave the last segments. """ if n_shave_prefix...
diffusers/scripts/convert_ddpm_original_checkpoint_to_diffusers.py/0
{ "file_path": "diffusers/scripts/convert_ddpm_original_checkpoint_to_diffusers.py", "repo_id": "diffusers", "token_count": 8490 }
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#!/usr/bin/env python3 import argparse import os import jax as jnp import numpy as onp import torch import torch.nn as nn from music_spectrogram_diffusion import inference from t5x import checkpoints from diffusers import DDPMScheduler, OnnxRuntimeModel, SpectrogramDiffusionPipeline from diffusers.pipelines.spectrogr...
diffusers/scripts/convert_music_spectrogram_to_diffusers.py/0
{ "file_path": "diffusers/scripts/convert_music_spectrogram_to_diffusers.py", "repo_id": "diffusers", "token_count": 4469 }
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import argparse import safetensors.torch from diffusers import AutoencoderTiny """ Example - From the diffusers root directory: Download the weights: ```sh $ wget -q https://huggingface.co/madebyollin/taesd/resolve/main/taesd_encoder.safetensors $ wget -q https://huggingface.co/madebyollin/taesd/resolve/main/taesd...
diffusers/scripts/convert_tiny_autoencoder_to_diffusers.py/0
{ "file_path": "diffusers/scripts/convert_tiny_autoencoder_to_diffusers.py", "repo_id": "diffusers", "token_count": 990 }
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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/commands/fp16_safetensors.py/0
{ "file_path": "diffusers/src/diffusers/commands/fp16_safetensors.py", "repo_id": "diffusers", "token_count": 2248 }
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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/single_file.py/0
{ "file_path": "diffusers/src/diffusers/loaders/single_file.py", "repo_id": "diffusers", "token_count": 5875 }
128
# Copyright 2024 Ollin Boer Bohan and The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless ...
diffusers/src/diffusers/models/autoencoders/autoencoder_tiny.py/0
{ "file_path": "diffusers/src/diffusers/models/autoencoders/autoencoder_tiny.py", "repo_id": "diffusers", "token_count": 6580 }
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from ..utils import deprecate from .transformers.prior_transformer import PriorTransformer, PriorTransformerOutput class PriorTransformerOutput(PriorTransformerOutput): deprecation_message = "Importing `PriorTransformerOutput` from `diffusers.models.prior_transformer` is deprecated and this will be removed in a f...
diffusers/src/diffusers/models/prior_transformer.py/0
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130
# coding=utf-8 # Copyright 2024 The HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable...
diffusers/src/diffusers/models/unets/uvit_2d.py/0
{ "file_path": "diffusers/src/diffusers/models/unets/uvit_2d.py", "repo_id": "diffusers", "token_count": 8290 }
131
# Copyright 2024 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
diffusers/src/diffusers/pipelines/audioldm/pipeline_audioldm.py/0
{ "file_path": "diffusers/src/diffusers/pipelines/audioldm/pipeline_audioldm.py", "repo_id": "diffusers", "token_count": 11533 }
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import html import inspect import re import urllib.parse as ul from typing import Any, Callable, Dict, List, Optional, Union import numpy as np import PIL.Image import torch from transformers import CLIPImageProcessor, T5EncoderModel, T5Tokenizer from ...loaders import LoraLoaderMixin from ...models import UNet2DCond...
diffusers/src/diffusers/pipelines/deepfloyd_if/pipeline_if_inpainting.py/0
{ "file_path": "diffusers/src/diffusers/pipelines/deepfloyd_if/pipeline_if_inpainting.py", "repo_id": "diffusers", "token_count": 21148 }
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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/audio_diffusion/pipeline_audio_diffusion.py/0
{ "file_path": "diffusers/src/diffusers/pipelines/deprecated/audio_diffusion/pipeline_audio_diffusion.py", "repo_id": "diffusers", "token_count": 6240 }
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import inspect from typing import Callable, List, Optional, Union import numpy as np import PIL.Image import torch from transformers import CLIPImageProcessor, CLIPTokenizer from ....configuration_utils import FrozenDict from ....schedulers import DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler from ....utils impo...
diffusers/src/diffusers/pipelines/deprecated/stable_diffusion_variants/pipeline_onnx_stable_diffusion_inpaint_legacy.py/0
{ "file_path": "diffusers/src/diffusers/pipelines/deprecated/stable_diffusion_variants/pipeline_onnx_stable_diffusion_inpaint_legacy.py", "repo_id": "diffusers", "token_count": 12042 }
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# Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) # William Peebles and Saining Xie # # Copyright (c) 2021 OpenAI # MIT License # # 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 wi...
diffusers/src/diffusers/pipelines/dit/pipeline_dit.py/0
{ "file_path": "diffusers/src/diffusers/pipelines/dit/pipeline_dit.py", "repo_id": "diffusers", "token_count": 4179 }
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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/kandinsky2_2/pipeline_kandinsky2_2_img2img.py/0
{ "file_path": "diffusers/src/diffusers/pipelines/kandinsky2_2/pipeline_kandinsky2_2_img2img.py", "repo_id": "diffusers", "token_count": 7964 }
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/src/diffusers/pipelines/ledits_pp/pipeline_leditspp_stable_diffusion_xl.py/0
{ "file_path": "diffusers/src/diffusers/pipelines/ledits_pp/pipeline_leditspp_stable_diffusion_xl.py", "repo_id": "diffusers", "token_count": 41594 }
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from dataclasses import dataclass from typing import List, Optional, Union import numpy as np import PIL.Image from ...utils import BaseOutput @dataclass class SemanticStableDiffusionPipelineOutput(BaseOutput): """ Output class for Stable Diffusion pipelines. Args: images (`List[PIL.Image.Image...
diffusers/src/diffusers/pipelines/semantic_stable_diffusion/pipeline_output.py/0
{ "file_path": "diffusers/src/diffusers/pipelines/semantic_stable_diffusion/pipeline_output.py", "repo_id": "diffusers", "token_count": 306 }
139
# Copyright 2024 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_flax_stable_diffusion_img2img.py/0
{ "file_path": "diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_flax_stable_diffusion_img2img.py", "repo_id": "diffusers", "token_count": 9901 }
140
# Copyright 2024 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_stable_unclip_img2img.py/0
{ "file_path": "diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_stable_unclip_img2img.py", "repo_id": "diffusers", "token_count": 17229 }
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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 i...
diffusers/src/diffusers/pipelines/stable_diffusion_panorama/__init__.py/0
{ "file_path": "diffusers/src/diffusers/pipelines/stable_diffusion_panorama/__init__.py", "repo_id": "diffusers", "token_count": 528 }
142
from typing import TYPE_CHECKING from ...utils import ( DIFFUSERS_SLOW_IMPORT, BaseOutput, OptionalDependencyNotAvailable, _LazyModule, get_objects_from_module, is_torch_available, is_transformers_available, ) _dummy_objects = {} _import_structure = {} try: if not (is_transformers_av...
diffusers/src/diffusers/pipelines/stable_video_diffusion/__init__.py/0
{ "file_path": "diffusers/src/diffusers/pipelines/stable_video_diffusion/__init__.py", "repo_id": "diffusers", "token_count": 664 }
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from typing import Optional import numpy as np import torch from torch import nn from transformers import GPT2Config, GPT2LMHeadModel from transformers.modeling_utils import ModuleUtilsMixin from ...configuration_utils import ConfigMixin, register_to_config from ...models import ModelMixin # Modified from ClipCapti...
diffusers/src/diffusers/pipelines/unidiffuser/modeling_text_decoder.py/0
{ "file_path": "diffusers/src/diffusers/pipelines/unidiffuser/modeling_text_decoder.py", "repo_id": "diffusers", "token_count": 6304 }
144
# Copyright 2024 Google Brain and The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless requ...
diffusers/src/diffusers/schedulers/deprecated/scheduling_sde_vp.py/0
{ "file_path": "diffusers/src/diffusers/schedulers/deprecated/scheduling_sde_vp.py", "repo_id": "diffusers", "token_count": 1693 }
145
# Copyright 2024 Katherine Crowson, The HuggingFace Team and hlky. 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_dpmsolver_sde.py/0
{ "file_path": "diffusers/src/diffusers/schedulers/scheduling_dpmsolver_sde.py", "repo_id": "diffusers", "token_count": 10658 }
146
# Copyright 2024 Zhejiang University Team and The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # #...
diffusers/src/diffusers/schedulers/scheduling_pndm_flax.py/0
{ "file_path": "diffusers/src/diffusers/schedulers/scheduling_pndm_flax.py", "repo_id": "diffusers", "token_count": 9597 }
147
# 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/utils/doc_utils.py/0
{ "file_path": "diffusers/src/diffusers/utils/doc_utils.py", "repo_id": "diffusers", "token_count": 506 }
148
# 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/utils/import_utils.py/0
{ "file_path": "diffusers/src/diffusers/utils/import_utils.py", "repo_id": "diffusers", "token_count": 9538 }
149
# 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/lora/test_lora_layers_sd.py/0
{ "file_path": "diffusers/tests/lora/test_lora_layers_sd.py", "repo_id": "diffusers", "token_count": 10772 }
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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_1d.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...
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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/ddim/test_ddim.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/kandinsky/test_kandinsky.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/kandinsky3/test_kandinsky3_img2img.py/0
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# These are canonical sets of parameters for different types of pipelines. # They are set on subclasses of `PipelineTesterMixin` as `params` and # `batch_params`. # # If a pipeline's set of arguments has minor changes from one of the common sets # of arguments, do not make modifications to the existing common sets of a...
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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_img2img.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_upscale.py/0
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import unittest from diffusers.pipelines.pipeline_utils import is_safetensors_compatible class IsSafetensorsCompatibleTests(unittest.TestCase): def test_all_is_compatible(self): filenames = [ "safety_checker/pytorch_model.bin", "safety_checker/model.safetensors", "vae/...
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import gc import random import traceback import unittest import numpy as np import torch from PIL import Image from transformers import ( CLIPImageProcessor, CLIPTextModel, CLIPTokenizer, CLIPVisionModelWithProjection, GPT2Tokenizer, ) from diffusers import ( AutoencoderKL, DPMSolverMultis...
diffusers/tests/pipelines/unidiffuser/test_unidiffuser.py/0
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import tempfile import torch from diffusers import ( DEISMultistepScheduler, DPMSolverMultistepScheduler, DPMSolverSinglestepScheduler, UniPCMultistepScheduler, ) from .test_schedulers import SchedulerCommonTest class DPMSolverSinglestepSchedulerTest(SchedulerCommonTest): scheduler_classes = (D...
diffusers/tests/schedulers/test_scheduler_dpm_single.py/0
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import torch from diffusers import UnCLIPScheduler from .test_schedulers import SchedulerCommonTest # UnCLIPScheduler is a modified DDPMScheduler with a subset of the configuration. class UnCLIPSchedulerTest(SchedulerCommonTest): scheduler_classes = (UnCLIPScheduler,) def get_scheduler_config(self, **kwarg...
diffusers/tests/schedulers/test_scheduler_unclip.py/0
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# coding=utf-8 # Copyright 2024 The HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable...
diffusers/utils/overwrite_expected_slice.py/0
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# Introduction <CourseFloatingBanner unit={0} classNames="absolute z-10 right-0 top-0" /> ## Bienvenue au cours sur les modèles de diffusion 🤗 ! ## À quoi s'attendre ? In this free course, you will: - 👩‍🎓 Study the theory behind diffusion models - 🧨 Learn how to generate images and audio with the popula...
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<jupyter_start><jupyter_text>Préparer des données (PyTorch) Installez les bibliothèques 🤗 *Transformers* et 🤗 *Datasets* pour exécuter ce *notebook*.<jupyter_code>!pip install datasets transformers[sentencepiece] import torch from transformers import AdamW, AutoTokenizer, AutoModelForSequenceClassification # Comme ...
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<jupyter_start><jupyter_text>Entraîner un nouveau *tokenizer* à partir d'un ancien Installez les bibliothèques 🤗 *Transformers* et 🤗 *Datasets* pour exécuter ce *notebook*.<jupyter_code>!pip install datasets transformers[sentencepiece] !apt install git-lfs<jupyter_output><empty_output><jupyter_text>Vous aurez besoin ...
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<jupyter_start><jupyter_text>Résumé (PyTorch) Installez les bibliothèques 🤗 *Datasets* et 🤗 *Transformers* pour exécuter ce *notebook*.<jupyter_code>!pip install datasets transformers[sentencepiece] !pip install accelerate # Pour exécuter l'entraînement sur TPU, vous devez décommenter la ligne suivante : # !pip insta...
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<jupyter_start><jupyter_text>Fonctions avancées d'Interface Installez les bibliothèques 🤗 Transformers et 🤗 Gradio pour exécuter ce *notebook*.<jupyter_code>!pip install datasets transformers[sentencepiece] !pip install gradio import random import gradio as gr def chat(message, history): history = history or [...
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<jupyter_start><jupyter_text>CLIP Guided Stable Diffusion using [d🧨ffusers](https://github.com/huggingface/diffusers) This notebook shows how to do CLIP guidance with Stable diffusion using diffusers libray. This allows you to use newly released [CLIP models by LAION AI.](https://huggingface.co/laion).This notebook is...
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<jupyter_start><jupyter_text>Run Dreambooth fine-tuned models for Stable Diffusion using d🧨ffusers This notebook allows you to run Stable Diffusion concepts trained via Dreambooth using 🤗 Hugging Face [🧨 Diffusers library](https://github.com/huggingface/diffusers). Train your own using [here]() and navigate the [pub...
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<jupyter_start><jupyter_text>Patch Time Series Transformer in HuggingFace - Getting StartedIn this blog, we provide examples of how to get started with PatchTST. We first demonstrate the forecasting capability of `PatchTST` on the Electricity data. We will then demonstrate the transfer learning capability of `PatchTST`...
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<jupyter_start><jupyter_text>Fine-tuning a 🤗 Transformers model on TPU with **Flax/JAX** In this notebook, we will see how to fine-tune one of the [🤗 Transformers](https://github.com/huggingface/transformers) models on TPU using [**Flax**](https://flax.readthedocs.io/en/latest/index.html). As can be seen on [this ben...
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<jupyter_start><jupyter_text>Huggingface Sagemaker-sdk - Distributed Training Demo Distributed Summarization with `transformers` scripts + `Trainer` and `samsum` dataset 1. [Tutorial](Tutorial) 2. [Set up a development environment and install sagemaker](Set-up-a-development-environment-and-install-sagemaker) 1. [In...
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import argparse import logging import os import random import sys import numpy as np import torch from datasets import load_from_disk, load_metric from transformers import AutoModelForSequenceClassification, AutoTokenizer, Trainer, TrainingArguments from transformers.trainer_utils import get_last_checkpoint if __name...
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<jupyter_start><jupyter_text>Serverless Inference with Hugging Face's Transformers & Amazon SageMaker Welcome to this getting started guide. We will use the Hugging Face Inference DLCs and Amazon SageMaker Python SDK to create a [Serverless Inference](https://docs.aws.amazon.com/sagemaker/latest/dg/serverless-endpoints...
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import base64 import torch from io import BytesIO from diffusers import StableDiffusionPipeline def model_fn(model_dir): # Load stable diffusion and move it to the GPU pipe = StableDiffusionPipeline.from_pretrained(model_dir, torch_dtype=torch.float16) pipe = pipe.to("cuda") return pipe def predict_fn(data,...
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import os import argparse from transformers import ( AutoModelForCausalLM, AutoTokenizer, set_seed, default_data_collator, ) from datasets import load_from_disk import torch from transformers import Seq2SeqTrainingArguments, Seq2SeqTrainer, DonutProcessor, VisionEncoderDecoderModel,VisionEncoderDecoderC...
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# docstyle-ignore INSTALL_CONTENT = """ # PEFT installation ! pip install peft accelerate transformers # To install from source instead of the last release, comment the command above and uncomment the following one. # ! pip install git+https://github.com/huggingface/peft.git """
peft/docs/source/_config.py/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...
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import os import torch import torch.nn as nn import transformers from datasets import load_dataset from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig from peft import LoraConfig, get_peft_model os.environ["CUDA_VISIBLE_DEVICES"] = "0" # -*- coding: utf-8 -*- """Finetune-opt-bnb-peft.i...
peft/examples/fp4_finetuning/finetune_fp4_opt_bnb_peft.py/0
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import argparse import os from typing import Dict import torch from diffusers import UNet2DConditionModel from safetensors.torch import save_file from transformers import CLIPTextModel from peft import PeftModel, get_peft_model_state_dict # Default kohya_ss LoRA replacement modules # https://github.com/kohya-ss/sd-...
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<jupyter_start><jupyter_code>import argparse import os import torch from torch.optim import AdamW from torch.utils.data import DataLoader from peft import ( get_peft_config, get_peft_model, get_peft_model_state_dict, set_peft_model_state_dict, PeftType, PrefixTuningConfig, PromptEncoderConf...
peft/examples/sequence_classification/P_Tuning.ipynb/0
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accelerate launch --config_file "configs/deepspeed_config_z3_qlora.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...
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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...
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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/adaption_prompt/config.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/lokr/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/prompt_tuning/config.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...
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#!/usr/bin/env python3 # coding=utf-8 # Copyright 2023-present the HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 #...
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""" Convert weights from https://github.com/google-research/nested-transformer NOTE: You'll need https://github.com/google/CommonLoopUtils, not included in requirements.txt """ import sys import numpy as np import torch from clu import checkpoint arch_depths = { 'nest_base': [2, 2, 20], 'nest_small': [2, 2...
pytorch-image-models/convert/convert_nest_flax.py/0
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# CSP-ResNeXt **CSPResNeXt** is a convolutional neural network where we apply the Cross Stage Partial Network (CSPNet) approach to [ResNeXt](https://paperswithcode.com/method/resnext). The CSPNet partitions the feature map of the base layer into two parts and then merges them through a cross-stage hierarchy. The use o...
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# HRNet **HRNet**, or **High-Resolution Net**, is a general purpose convolutional neural network for tasks like semantic segmentation, object detection and image classification. It is able to maintain high resolution representations through the whole process. We start from a high-resolution convolution stream, gradual...
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# RegNetY **RegNetY** is a convolutional network design space with simple, regular models with parameters: depth $d$, initial width $w\_{0} > 0$, and slope $w\_{a} > 0$, and generates a different block width $u\_{j}$ for each block $j < d$. The key restriction for the RegNet types of model is that there is a linear pa...
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# SWSL ResNet **Residual Networks**, or **ResNets**, learn residual functions with reference to the layer inputs, instead of learning unreferenced functions. Instead of hoping each few stacked layers directly fit a desired underlying mapping, residual nets let these layers fit a residual mapping. They stack [residual ...
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# CSP-ResNet **CSPResNet** is a convolutional neural network where we apply the Cross Stage Partial Network (CSPNet) approach to [ResNet](https://paperswithcode.com/method/resnet). The CSPNet partitions the feature map of the base layer into two parts and then merges them through a cross-stage hierarchy. The use of a ...
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# (Gluon) Xception **Xception** is a convolutional neural network architecture that relies solely on [depthwise separable convolution](https://paperswithcode.com/method/depthwise-separable-convolution) layers. The weights from this model were ported from [Gluon](https://cv.gluon.ai/model_zoo/classification.html). ##...
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# RegNetX **RegNetX** is a convolutional network design space with simple, regular models with parameters: depth $d$, initial width $w\_{0} > 0$, and slope $w\_{a} > 0$, and generates a different block width $u\_{j}$ for each block $j < d$. The key restriction for the RegNet types of model is that there is a linear pa...
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# SSL ResNeXT A **ResNeXt** repeats a [building block](https://paperswithcode.com/method/resnext-block) that aggregates a set of transformations with the same topology. Compared to a [ResNet](https://paperswithcode.com/method/resnet), it exposes a new dimension, *cardinality* (the size of the set of transformations) ...
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# Hugging Face Timm Docs ## Getting Started ``` pip install git+https://github.com/huggingface/doc-builder.git@main#egg=hf-doc-builder pip install watchdog black ``` ## Preview the Docs Locally ``` doc-builder preview timm hfdocs/source ```
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