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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/index.md/0
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<!--Copyright 2024 Custom Diffusion authors 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...
diffusers/docs/source/ko/training/custom_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/ko/using-diffusers/img2img.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/advanced_diffusion_training/train_dreambooth_lora_flux_advanced.py/0
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import inspect from typing import Any, Callable, Dict, List, Optional, Union import numpy as np import torch from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer from diffusers.image_processor import VaeImageProcessor from diffusers.loaders import FromSingleFileMixin, StableDiffusionLoraLoaderMix...
diffusers/examples/community/latent_consistency_interpolate.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/community/pipeline_animatediff_img2video.py/0
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import types from typing import List, Optional, Tuple, Union import torch from transformers import CLIPTextModelWithProjection, CLIPTokenizer from transformers.models.clip.modeling_clip import CLIPTextModelOutput from diffusers.models import PriorTransformer from diffusers.pipelines import DiffusionPipeline, StableDi...
diffusers/examples/community/stable_unclip.py/0
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# ControlNet training example [Adding Conditional Control to Text-to-Image Diffusion Models](https://arxiv.org/abs/2302.05543) by Lvmin Zhang and Maneesh Agrawala. This example is based on the [training example in the original ControlNet repository](https://github.com/lllyasviel/ControlNet/blob/main/docs/train.md). I...
diffusers/examples/controlnet/README.md/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/examples/dreambooth/test_dreambooth.py/0
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# InstructPix2Pix text-to-edit-image fine-tuning This extended LoRA training script was authored by [Aiden-Frost](https://github.com/Aiden-Frost). This is an experimental LoRA extension of [this example](https://github.com/huggingface/diffusers/blob/main/examples/instruct_pix2pix/train_instruct_pix2pix.py). This script...
diffusers/examples/research_projects/instructpix2pix_lora/README.md/0
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# coding=utf-8 # Copyright 2023 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
diffusers/examples/research_projects/pixart/train_pixart_controlnet_hf.py/0
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import argparse import copy import itertools import logging import math import os import random import shutil from pathlib import Path import numpy as np import torch import torch.nn.functional as F import torch.utils.checkpoint import torchvision.transforms.v2 as transforms_v2 import transformers from accelerate impo...
diffusers/examples/research_projects/realfill/train_realfill.py/0
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# VAE `vae_roundtrip.py` Demonstrates the use of a VAE by roundtripping an image through the encoder and decoder. Original and reconstructed images are displayed side by side. ``` cd examples/research_projects/vae python vae_roundtrip.py \ --pretrained_model_name_or_path="stable-diffusion-v1-5/stable-diffusion-v1...
diffusers/examples/research_projects/vae/README.md/0
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import argparse from typing import Any, Dict import torch from huggingface_hub import hf_hub_download from safetensors.torch import load_file from diffusers import AutoencoderDC def remap_qkv_(key: str, state_dict: Dict[str, Any]): qkv = state_dict.pop(key) q, k, v = torch.chunk(qkv, 3, dim=0) parent_mo...
diffusers/scripts/convert_dcae_to_diffusers.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/scripts/convert_original_t2i_adapter.py/0
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# Convert the original UniDiffuser checkpoints into diffusers equivalents. import argparse from argparse import Namespace import torch from transformers import ( CLIPImageProcessor, CLIPTextConfig, CLIPTextModel, CLIPTokenizer, CLIPVisionConfig, CLIPVisionModelWithProjection, GPT2Tokenizer...
diffusers/scripts/convert_unidiffuser_to_diffusers.py/0
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# coding=utf-8 # Copyright 2025 The HuggingFace Inc. team. # Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.a...
diffusers/src/diffusers/configuration_utils.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/lora_pipeline.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/attention_flax.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/vq_model.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/downsampling.py/0
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# Copyright 2024 ConsisID 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/models/transformers/consisid_transformer_3d.py/0
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# Copyright 2024 The Genmo team and The HuggingFace Team. # All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless ...
diffusers/src/diffusers/models/transformers/transformer_ltx.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_motion_model.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/pipelines/auto_pipeline.py/0
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import importlib.util import os import cv2 import numpy as np import torch from PIL import Image, ImageOps from torchvision.transforms import InterpolationMode from torchvision.transforms.functional import normalize, resize from ...utils import load_image _insightface_available = importlib.util.find_spec("insightfa...
diffusers/src/diffusers/pipelines/consisid/consisid_utils.py/0
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# Copyright 2022 The Music Spectrogram Diffusion Authors. # Copyright 2024 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache...
diffusers/src/diffusers/pipelines/deprecated/spectrogram_diffusion/notes_encoder.py/0
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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/versatile_diffusion/pipeline_versatile_diffusion_text_to_image.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/kandinsky/pipeline_kandinsky_inpaint.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 applicabl...
diffusers/src/diffusers/pipelines/ledits_pp/pipeline_leditspp_stable_diffusion_xl.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/pipeline_stable_diffusion_image_variation.py/0
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import inspect import warnings from typing import Callable, List, Optional, Union import numpy as np import torch from packaging import version from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer, CLIPVisionModelWithProjection from ...configuration_utils import FrozenDict from ...image_processor...
diffusers/src/diffusers/pipelines/stable_diffusion_safe/pipeline_stable_diffusion_safe.py/0
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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 is...
diffusers/src/diffusers/pipelines/wuerstchen/__init__.py/0
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from typing import TYPE_CHECKING, Any, Dict, List, Optional, Union from ..base import DiffusersQuantizer if TYPE_CHECKING: from ...models.modeling_utils import ModelMixin from ...utils import ( get_module_from_name, is_accelerate_available, is_accelerate_version, is_gguf_available, is_gguf_...
diffusers/src/diffusers/quantizers/gguf/gguf_quantizer.py/0
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# Copyright 2024 Stanford University Team and The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # #...
diffusers/src/diffusers/schedulers/scheduling_ddim_flax.py/0
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# Copyright 2024 Shuchen Xue, etc. in University of Chinese Academy of Sciences 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 # # htt...
diffusers/src/diffusers/schedulers/scheduling_sasolver.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 FlaxControlNetModel(metaclass=DummyObject): _backends = ["flax"] def __init__(self, *args, **kwargs): requires_backends(self, ["flax"]) @classmethod def from_c...
diffusers/src/diffusers/utils/dummy_flax_objects.py/0
{ "file_path": "diffusers/src/diffusers/utils/dummy_flax_objects.py", "repo_id": "diffusers", "token_count": 2343 }
import os import tempfile from typing import Any, Callable, List, Optional, Tuple, Union from urllib.parse import unquote, urlparse import PIL.Image import PIL.ImageOps import requests from .import_utils import BACKENDS_MAPPING, is_imageio_available def load_image( image: Union[str, PIL.Image.Image], convert_me...
diffusers/src/diffusers/utils/loading_utils.py/0
{ "file_path": "diffusers/src/diffusers/utils/loading_utils.py", "repo_id": "diffusers", "token_count": 2302 }
# 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/hooks/test_hooks.py/0
{ "file_path": "diffusers/tests/hooks/test_hooks.py", "repo_id": "diffusers", "token_count": 6203 }
# 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_hunyuan_video.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/models/transformers/test_models_transformer_sana.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/others/test_config.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/controlnet/test_controlnet_sdxl.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/dance_diffusion/test_dance_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/pag/test_pag_hunyuan_dit.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...
diffusers/tests/pipelines/pipeline_params.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_depth.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_xl/test_stable_diffusion_xl_adapter.py/0
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from diffusers.utils.testing_utils import require_onnxruntime @require_onnxruntime class OnnxPipelineTesterMixin: """ This mixin is designed to be used with unittest.TestCase classes. It provides a set of common tests for each ONNXRuntime pipeline, e.g. saving and loading the pipeline, equivalence of ...
diffusers/tests/pipelines/test_pipelines_onnx_common.py/0
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import torch from diffusers import TCDScheduler from .test_schedulers import SchedulerCommonTest class TCDSchedulerTest(SchedulerCommonTest): scheduler_classes = (TCDScheduler,) forward_default_kwargs = (("num_inference_steps", 10),) def get_scheduler_config(self, **kwargs): config = { ...
diffusers/tests/schedulers/test_scheduler_tcd.py/0
{ "file_path": "diffusers/tests/schedulers/test_scheduler_tcd.py", "repo_id": "diffusers", "token_count": 3098 }
import gc import unittest import torch from diffusers import ( StableDiffusionImg2ImgPipeline, ) from diffusers.utils import load_image from diffusers.utils.testing_utils import ( backend_empty_cache, enable_full_determinism, require_torch_accelerator, slow, torch_device, ) from .single_file_...
diffusers/tests/single_file/test_stable_diffusion_img2img_single_file.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/benchmarks/video/run_video_benchmark.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/__init__.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/transforms.py/0
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#!/usr/bin/env python # Copyright 2024 Tony Z. Zhao and 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...
lerobot/lerobot/common/policies/act/modeling_act.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/policies/utils.py/0
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"""Logic to calibrate a robot arm built with feetech motors""" # TODO(rcadene, aliberts): move this logic into the robot code when refactoring import time import numpy as np from lerobot.common.robot_devices.motors.feetech import ( CalibrationMode, TorqueMode, convert_degrees_to_steps, ) from lerobot.com...
lerobot/lerobot/common/robot_devices/robots/feetech_calibration.py/0
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""" This script configure a single motor at a time to a given ID and baudrate. Example of usage: ```bash python lerobot/scripts/configure_motor.py \ --port /dev/tty.usbmodem585A0080521 \ --brand feetech \ --model sts3215 \ --baudrate 1000000 \ --ID 1 ``` """ import argparse import time def get_motor_bus_c...
lerobot/lerobot/scripts/configure_motor.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/test_datasets.py/0
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<!--โš ๏ธ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be rendered properly in your Markdown viewer. --> # Configuration [`PeftConfigMixin`] is the base configuration class for storing the adapter configuration of a [`PeftModel`], and [`PromptLearningCo...
peft/docs/source/package_reference/config.md/0
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<!--โš ๏ธ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be rendered properly in your Markdown viewer. --> # Models [`PeftModel`] is the base model class for specifying the base Transformer model and configuration to apply a PEFT method to. The base `Peft...
peft/docs/source/package_reference/peft_model.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/examples/boft_controlnet/boft_controlnet.md/0
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<jupyter_start><jupyter_text>Training PEFT models with new tokens being added to the embedding layers and tokenizerIn this example, we will learn how to train a LoRA model when adding new tokens to the tokenizer and model. This is a common usecase when doing the following:1. Instruction finetuning with new tokens beind...
peft/examples/causal_language_modeling/peft_lora_clm_with_additional_tokens.ipynb/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/examples/feature_extraction/peft_lora_embedding_semantic_search.py/0
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<jupyter_start><jupyter_text>Using PEFT with timm `peft` allows us to train any model with LoRA as long as the layer type is supported. Since `Conv2D` is one of the supported layer types, it makes sense to test it on image models.In this short notebook, we will demonstrate this with an image classification task using [...
peft/examples/image_classification/image_classification_timm_peft_lora.ipynb/0
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<jupyter_start><jupyter_text>Using FourierFT for sequence classification In this example, we fine-tune Roberta (base) on a sequence classification task using FourierFT. Imports<jupyter_code># To run this notebook, please run `pip install evaluate` to install additional dependencies not covered by PEFT. import torch f...
peft/examples/sequence_classification/FourierFT.ipynb/0
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# Copyright 2024-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/mapping_func.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/adaption_prompt/layer.py/0
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# Copyright 2024-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/cpt/model.py/0
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# Copyright 2024-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/ln_tuning/layer.py/0
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# Copyright 2024-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/dora.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/oft/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/prompt_tuning/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/utils/__init__.py/0
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# Copyright 2024-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/tests/test_boft.py/0
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# Copyright 2024-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/tests/test_loraplus.py/0
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#!/usr/bin/env python3 """ Checkpoint Cleaning Script Takes training checkpoints with GPU tensors, optimizer state, extra dict keys, etc. and outputs a CPU tensor checkpoint with only the `state_dict` along with SHA256 calculation for model zoo compatibility. Hacked together by / Copyright 2020 Ross Wightman (https:...
pytorch-image-models/clean_checkpoint.py/0
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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 i...
pytorch-image-models/hfdocs/source/models/regnetx.mdx/0
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# Results CSV files containing an ImageNet-1K and out-of-distribution (OOD) test set validation results for all models with pretrained weights is located in the repository [results folder](https://github.com/rwightman/pytorch-image-models/tree/master/results). ## Self-trained Weights The table below includes ImageNe...
pytorch-image-models/hfdocs/source/results.mdx/0
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import logging from .constants import * _logger = logging.getLogger(__name__) def resolve_data_config( args=None, pretrained_cfg=None, model=None, use_test_size=False, verbose=False ): assert model or args or pretrained_cfg, "At least one of model, args, or pretrained_cfg...
pytorch-image-models/timm/data/config.py/0
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""" Dataset reader for HF IterableDataset """ import math import os from itertools import repeat, chain from typing import Optional import torch import torch.distributed as dist from PIL import Image try: import datasets from datasets.distributed import split_dataset_by_node from datasets.splits import Sp...
pytorch-image-models/timm/data/readers/reader_hfids.py/0
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from typing import Optional import torch import torch.nn as nn import torch.nn.functional as F from .config import use_fused_attn from .mlp import Mlp from .weight_init import trunc_normal_tf_ class AttentionPoolLatent(nn.Module): """ Attention pooling w/ latent query """ fused_attn: torch.jit.Final[boo...
pytorch-image-models/timm/layers/attention_pool.py/0
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""" ECA module from ECAnet paper: ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks https://arxiv.org/abs/1910.03151 Original ECA model borrowed from https://github.com/BangguWu/ECANet Modified circular ECA implementation and adaption for use in timm package by Chris Ha https://github.com/V...
pytorch-image-models/timm/layers/eca.py/0
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""" Linear layer (alternate definition) """ import torch import torch.nn.functional as F from torch import nn as nn class Linear(nn.Linear): r"""Applies a linear transformation to the incoming data: :math:`y = xA^T + b` Wraps torch.nn.Linear to support AMP + torchscript usage by manually casting weight &...
pytorch-image-models/timm/layers/linear.py/0
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""" Depthwise Separable Conv Modules Basic DWS convs. Other variations of DWS exist with batch norm or activations between the DW and PW convs such as the Depthwise modules in MobileNetV2 / EfficientNet and Xception. Hacked together by / Copyright 2020 Ross Wightman """ from torch import nn as nn from .create_conv2d...
pytorch-image-models/timm/layers/separable_conv.py/0
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import dataclasses import logging import os from copy import deepcopy from pathlib import Path from typing import Any, Callable, Dict, List, Optional, Tuple, Union from torch import nn as nn from torch.hub import load_state_dict_from_url from timm.models._features import FeatureListNet, FeatureDictNet, FeatureHookNet...
pytorch-image-models/timm/models/_builder.py/0
{ "file_path": "pytorch-image-models/timm/models/_builder.py", "repo_id": "pytorch-image-models", "token_count": 8732 }
""" Model Registry Hacked together by / Copyright 2020 Ross Wightman """ import fnmatch import re import sys import warnings from collections import defaultdict, deque from copy import deepcopy from dataclasses import replace from typing import Any, Callable, Dict, Iterable, List, Optional, Set, Sequence, Union, Tuple...
pytorch-image-models/timm/models/_registry.py/0
{ "file_path": "pytorch-image-models/timm/models/_registry.py", "repo_id": "pytorch-image-models", "token_count": 5725 }
""" EdgeNeXt Paper: `EdgeNeXt: Efficiently Amalgamated CNN-Transformer Architecture for Mobile Vision Applications` - https://arxiv.org/abs/2206.10589 Original code and weights from https://github.com/mmaaz60/EdgeNeXt Modifications and additions for timm by / Copyright 2022, Ross Wightman """ import math from funct...
pytorch-image-models/timm/models/edgenext.py/0
{ "file_path": "pytorch-image-models/timm/models/edgenext.py", "repo_id": "pytorch-image-models", "token_count": 11055 }
""" PP-HGNet (V1 & V2) Reference: https://github.com/PaddlePaddle/PaddleClas/blob/develop/docs/zh_CN/models/ImageNet1k/PP-HGNetV2.md The Paddle Implement of PP-HGNet (https://github.com/PaddlePaddle/PaddleClas/blob/release/2.5.1/docs/en/models/PP-HGNet_en.md) PP-HGNet: https://github.com/PaddlePaddle/PaddleClas/blob/r...
pytorch-image-models/timm/models/hgnet.py/0
{ "file_path": "pytorch-image-models/timm/models/hgnet.py", "repo_id": "pytorch-image-models", "token_count": 13177 }
""" MobileViT Paper: V1: `MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer` - https://arxiv.org/abs/2110.02178 V2: `Separable Self-attention for Mobile Vision Transformers` - https://arxiv.org/abs/2206.02680 MobileVitBlock and checkpoints adapted from https://github.com/apple/ml-cvnets...
pytorch-image-models/timm/models/mobilevit.py/0
{ "file_path": "pytorch-image-models/timm/models/mobilevit.py", "repo_id": "pytorch-image-models", "token_count": 12812 }
"""PyTorch ResNet This started as a copy of https://github.com/pytorch/vision 'resnet.py' (BSD-3-Clause) with additional dropout and dynamic global avg/max pool. ResNeXt, SE-ResNeXt, SENet, and MXNet Gluon stem/downsample variants, tiered stems added by Ross Wightman Copyright 2019, Ross Wightman """ import math fro...
pytorch-image-models/timm/models/resnet.py/0
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""" Vision Transformer (ViT) in PyTorch A PyTorch implement of Vision Transformers as described in: 'An Image Is Worth 16 x 16 Words: Transformers for Image Recognition at Scale' - https://arxiv.org/abs/2010.11929 `How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers` - https:...
pytorch-image-models/timm/models/vision_transformer.py/0
{ "file_path": "pytorch-image-models/timm/models/vision_transformer.py", "repo_id": "pytorch-image-models", "token_count": 79510 }
""" Adafactor (Big Vision variant) for PyTorch Adapted from the implementation in big vision: https://github.com/google-research/big_vision Described in 'Scaling Vision Transformers': https://arxiv.org/abs/2106.04560 Adaptation and PyTorch modifications by Ross Wightman """ from typing import List, Optional, Tuple, ...
pytorch-image-models/timm/optim/adafactor_bv.py/0
{ "file_path": "pytorch-image-models/timm/optim/adafactor_bv.py", "repo_id": "pytorch-image-models", "token_count": 6213 }
""" Nvidia NovoGrad Optimizer. Original impl by Nvidia from Jasper example: - https://github.com/NVIDIA/DeepLearningExamples/blob/master/PyTorch/SpeechRecognition/Jasper Paper: `Stochastic Gradient Methods with Layer-wise Adaptive Moments for Training of Deep Networks` - https://arxiv.org/abs/1905.11286 """ im...
pytorch-image-models/timm/optim/nvnovograd.py/0
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from .agc import adaptive_clip_grad from .attention_extract import AttentionExtract from .checkpoint_saver import CheckpointSaver from .clip_grad import dispatch_clip_grad from .cuda import ApexScaler, NativeScaler from .decay_batch import decay_batch_step, check_batch_size_retry from .distributed import distribute_bn,...
pytorch-image-models/timm/utils/__init__.py/0
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""" Summary utilities Hacked together by / Copyright 2020 Ross Wightman """ import csv import os from collections import OrderedDict try: import wandb except ImportError: pass def get_outdir(path, *paths, inc=False): outdir = os.path.join(path, *paths) if not os.path.exists(outdir): os.maked...
pytorch-image-models/timm/utils/summary.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...
smolagents/docs/source/en/tutorials/secure_code_execution.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...
smolagents/docs/source/hi/tutorials/tools.md/0
{ "file_path": "smolagents/docs/source/hi/tutorials/tools.md", "repo_id": "smolagents", "token_count": 10845 }
# This is a config for E2B sandbox template. # You can use template ID (qywp2ctmu2q7jzprcf4j) to create a sandbox: # Python SDK # from e2b import Sandbox, AsyncSandbox # sandbox = Sandbox("qywp2ctmu2q7jzprcf4j") # Sync sandbox # sandbox = await AsyncSandbox.create("qywp2ctmu2q7jzprcf4j") # Async sandbox # JS SDK # im...
smolagents/e2b.toml/0
{ "file_path": "smolagents/e2b.toml", "repo_id": "smolagents", "token_count": 254 }
from typing import Optional from smolagents import Tool from smolagents.models import MessageRole, Model from .mdconvert import MarkdownConverter class TextInspectorTool(Tool): name = "inspect_file_as_text" description = """ You cannot load files yourself: instead call this tool to read a file as markdown t...
smolagents/examples/open_deep_research/scripts/text_inspector_tool.py/0
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