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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/push_to_hub.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/index.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/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/ko/training/instructpix2pix.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/loading.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/pt/quicktour.md/0
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import glob import os from typing import Dict, List, Union import safetensors.torch import torch from huggingface_hub import snapshot_download from huggingface_hub.utils import validate_hf_hub_args from diffusers import DiffusionPipeline, __version__ from diffusers.schedulers.scheduling_utils import SCHEDULER_CONFIG_...
diffusers/examples/community/checkpoint_merger.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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# Inference Examples **The inference examples folder is deprecated and will be removed in a future version**. **Officially supported inference examples can be found in the [Pipelines folder](https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines)**. - For `Image-to-Image text-guided generation wit...
diffusers/examples/inference/README.md/0
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import d4rl # noqa import gym import tqdm from diffusers.experimental import ValueGuidedRLPipeline config = { "n_samples": 64, "horizon": 32, "num_inference_steps": 20, "n_guide_steps": 2, # can set to 0 for faster sampling, does not use value network "scale_grad_by_std": True, "scale": 0.1,...
diffusers/examples/reinforcement_learning/run_diffuser_locomotion.py/0
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# Multi Subject Dreambooth for Inpainting Models Please note that this project is not actively maintained. However, you can open an issue and tag @gzguevara. [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. Thi...
diffusers/examples/research_projects/multi_subject_dreambooth_inpainting/README.md/0
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## Training examples Creating a training image set is [described in a different document](https://huggingface.co/docs/datasets/image_process#image-datasets). ### Installing the dependencies Before running the scripts, make sure to install the library's training dependencies: **Important** To make sure you can succ...
diffusers/examples/research_projects/onnxruntime/unconditional_image_generation/README.md/0
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import argparse from typing import Dict import torch import torch.nn as nn from diffusers import SparseControlNetModel KEYS_RENAME_MAPPING = { ".attention_blocks.0": ".attn1", ".attention_blocks.1": ".attn2", ".attn1.pos_encoder": ".pos_embed", ".ff_norm": ".norm3", ".norms.0": ".norm1", ".n...
diffusers/scripts/convert_animatediff_sparsectrl_to_diffusers.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/scripts/convert_original_controlnet_to_diffusers.py/0
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import argparse from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline if __name__ == "__main__": parser = argparse.ArgumentParser() parser.add_argument("--dump_path", default=None, type=str, required=True, help="Path to...
diffusers/scripts/convert_unclip_txt2img_to_image_variation.py/0
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# coding=utf-8 # Copyright 2024 The HuggingFace Inc. team. # Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.a...
diffusers/src/diffusers/configuration_utils.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/src/diffusers/loaders/single_file_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/models/autoencoders/autoencoder_kl_temporal_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/src/diffusers/models/lora.py/0
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# Copyright 2024 the Latte 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 re...
diffusers/src/diffusers/models/transformers/latte_transformer_3d.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_2d_condition.py/0
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from typing import TYPE_CHECKING from ...utils import ( DIFFUSERS_SLOW_IMPORT, OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_transformers_available, ) _dummy_objects = {} _import_structure = {} try: if not (is_transformers_available() and is_torch_available()): ...
diffusers/src/diffusers/pipelines/amused/__init__.py/0
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from typing import TYPE_CHECKING from ...utils import DIFFUSERS_SLOW_IMPORT, _LazyModule _import_structure = {"pipeline_ddim": ["DDIMPipeline"]} if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT: from .pipeline_ddim import DDIMPipeline else: import sys sys.modules[__name__] = _LazyModule( __name__, ...
diffusers/src/diffusers/pipelines/ddim/__init__.py/0
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from typing import TYPE_CHECKING from ...utils import ( DIFFUSERS_SLOW_IMPORT, OptionalDependencyNotAvailable, _LazyModule, get_objects_from_module, is_librosa_available, is_note_seq_available, is_torch_available, is_transformers_available, ) _dummy_objects = {} _import_structure = {}...
diffusers/src/diffusers/pipelines/deprecated/__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/score_sde_ve/pipeline_score_sde_ve.py/0
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from typing import Any, Dict, List, Optional, Tuple, Union import numpy as np import torch import torch.nn as nn import torch.nn.functional as F from diffusers.utils import deprecate from ....configuration_utils import ConfigMixin, register_to_config from ....models import ModelMixin from ....models.activations impo...
diffusers/src/diffusers/pipelines/deprecated/versatile_diffusion/modeling_text_unet.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/kandinsky2_2/pipeline_kandinsky2_2_inpainting.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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# Copyright 2024 Open AI 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 required ...
diffusers/src/diffusers/pipelines/shap_e/pipeline_shap_e.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_k_diffusion/pipeline_stable_diffusion_k_diffusion.py/0
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# Copyright 2024 Kakao Brain and The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless requi...
diffusers/src/diffusers/pipelines/unclip/pipeline_unclip.py/0
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# Schedulers For more information on the schedulers, please refer to the [docs](https://huggingface.co/docs/diffusers/api/schedulers/overview).
diffusers/src/diffusers/schedulers/README.md/0
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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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# 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_flux.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_unet_blocks_common.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/cogvideox/test_cogvideox.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/kolors/test_kolors_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.py/0
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import contextlib import gc import inspect import io import json import os import re import tempfile import unittest import uuid from typing import Any, Callable, Dict, Union import numpy as np import PIL.Image import torch import torch.nn as nn from huggingface_hub import ModelCard, delete_repo from huggingface_hub.u...
diffusers/tests/pipelines/test_pipelines_common.py/0
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import gc import unittest import torch from diffusers import StableDiffusionXLInstructPix2PixPipeline from diffusers.utils.testing_utils import ( enable_full_determinism, require_torch_gpu, slow, ) enable_full_determinism() @slow @require_torch_gpu class StableDiffusionXLInstructPix2PixPipeline(unitte...
diffusers/tests/single_file/test_stable_diffusion_xl_instruct_pix2pix.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_slack_about_release.py/0
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.PHONY: tests PYTHON_PATH := $(shell which python) # If Poetry is installed, redefine PYTHON_PATH to use the Poetry-managed Python POETRY_CHECK := $(shell command -v poetry) ifneq ($(POETRY_CHECK),) PYTHON_PATH := $(shell poetry run which python) endif export PATH := $(dir $(PYTHON_PATH)):$(PATH) DEVICE ?= cpu bu...
lerobot/Makefile/0
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In this tutorial we will learn how to adapt a policy configuration to be compatible with a new environment and dataset. As a concrete example, we will adapt the default configuration for ACT to be compatible with the PushT environment and dataset. If you haven't already read our tutorial on the [training script and co...
lerobot/examples/advanced/1_train_act_pusht/train_act_pusht.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/push_dataset_to_hub/utils.py/0
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#!/usr/bin/env python # Copyright 2024 Nicklas Hansen, Xiaolong Wang, Hao Su, # 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 # # ht...
lerobot/lerobot/common/policies/tdmpc/configuration_tdmpc.py/0
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# @package _global_ # Defaults for training for the PushT dataset. seed: 100000 dataset_repo_id: lerobot/pusht override_dataset_stats: # TODO(rcadene, alexander-soare): should we remove image stats as well? do we use a pretrained vision model? observation.image: mean: [[[0.5]], [[0.5]], [[0.5]]] # (c,1,1) ...
lerobot/lerobot/configs/policy/vqbet.yaml/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 # # ...
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# Training Parler-TTS <a target="_blank" href="https://github.com/ylacombe/scripts_and_notebooks/blob/main/Finetuning_Parler_TTS_v1_on_a_single_speaker_dataset.ipynb"> <img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"/> </a> **TL;DR:** After having followed the [installation ...
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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. --> # Fully Sharded Data Parallel [Fully sharded data parallel](https://pytorch.org/docs/stable/fsdp.html) (FSDP) is developed for distributed training ...
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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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<jupyter_start><jupyter_text>Fine-tuning [Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on [timdettmers/openassistant-guanaco](https://huggingface.co/datasets/timdettmers/openassistant-guanaco) Dataset using QDora (quantized Lora w/ use_dora=True) on T4 Free Colab GPU.<jupyter_code># Install the librar...
peft/examples/dora_finetuning/QDoRA_finetuning.ipynb/0
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import argparse import os from collections import Counter from dataclasses import dataclass from typing import Dict, Optional import safetensors import torch from diffusers import UNet2DConditionModel from transformers import CLIPTextModel from peft import LoraConfig, get_peft_model, get_peft_model_state_dict, set_pe...
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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...
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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...
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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...
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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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#!/usr/bin/env python3 """ Checkpoint Averaging Script This script averages all model weights for checkpoints in specified path that match the specified filter wildcard. All checkpoints must be from the exact same model. For any hope of decent results, the checkpoints should be from the same or child (via resumes) tr...
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# AdvProp (EfficientNet) **AdvProp** is an adversarial training scheme which treats adversarial examples as additional examples, to prevent overfitting. Key to the method is the usage of a separate auxiliary batch norm for adversarial examples, as they have different underlying distributions to normal examples. The w...
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# NASNet **NASNet** is a type of convolutional neural network discovered through neural architecture search. The building blocks consist of normal and reduction cells. ## How do I use this model on an image? To load a pretrained model: ```py >>> import timm >>> model = timm.create_model('nasnetalarge', pretrained=T...
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# SK-ResNeXt **SK ResNeXt** is a variant of a [ResNeXt](https://www.paperswithcode.com/method/resnext) that employs a [Selective Kernel](https://paperswithcode.com/method/selective-kernel) unit. In general, all the large kernel convolutions in the original bottleneck blocks in ResNext are replaced by the proposed [SK ...
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# Models [[autodoc]] timm.create_model [[autodoc]] timm.list_models
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""" AutoAugment, RandAugment, AugMix, and 3-Augment for PyTorch This code implements the searched ImageNet policies with various tweaks and improvements and does not include any of the search code. AA and RA Implementation adapted from: https://github.com/tensorflow/tpu/blob/master/models/official/efficientnet/au...
pytorch-image-models/timm/data/auto_augment.py/0
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""" Dataset reader that wraps Hugging Face datasets Hacked together by / Copyright 2022 Ross Wightman """ import io import math from typing import Optional import torch import torch.distributed as dist from PIL import Image try: import datasets except ImportError as e: print("Please install Hugging Face data...
pytorch-image-models/timm/data/readers/reader_hfds.py/0
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from typing import List, Optional, Union import torch from torch import nn as nn from torch.nn import functional as F from .config import use_fused_attn from .create_conv2d import create_conv2d from .helpers import to_2tuple from .pool2d_same import create_pool2d class MultiQueryAttentionV2(nn.Module): """Multi...
pytorch-image-models/timm/layers/attention2d.py/0
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""" DropBlock, DropPath PyTorch implementations of DropBlock and DropPath (Stochastic Depth) regularization layers. Papers: DropBlock: A regularization method for convolutional networks (https://arxiv.org/abs/1810.12890) Deep Networks with Stochastic Depth (https://arxiv.org/abs/1603.09382) Code: DropBlock impl ins...
pytorch-image-models/timm/layers/drop.py/0
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import torch from torch import nn class LayerScale(nn.Module): """ LayerScale on tensors with channels in last-dim. """ def __init__( self, dim: int, init_values: float = 1e-5, inplace: bool = False, ) -> None: super().__init__() self.inp...
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""" Selective Kernel Convolution/Attention Paper: Selective Kernel Networks (https://arxiv.org/abs/1903.06586) Hacked together by / Copyright 2020 Ross Wightman """ import torch from torch import nn as nn from .conv_bn_act import ConvNormAct from .helpers import make_divisible from .trace_utils import _assert def ...
pytorch-image-models/timm/layers/selective_kernel.py/0
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from .beit import * from .byoanet import * from .byobnet import * from .cait import * from .coat import * from .convit import * from .convmixer import * from .convnext import * from .crossvit import * from .cspnet import * from .davit import * from .deit import * from .densenet import * from .dla import * from .dpn imp...
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""" PyTorch implementation of DualPathNetworks Based on original MXNet implementation https://github.com/cypw/DPNs with many ideas from another PyTorch implementation https://github.com/oyam/pytorch-DPNs. This implementation is compatible with the pretrained weights from cypw's MXNet implementation. Hacked together b...
pytorch-image-models/timm/models/dpn.py/0
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from ._builder import * from ._helpers import * from ._manipulate import * from ._prune import * import warnings warnings.warn(f"Importing from {__name__} is deprecated, please import via timm.models", DeprecationWarning)
pytorch-image-models/timm/models/helpers.py/0
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""" 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
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"""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...
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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
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""" Adan Optimizer Adan: Adaptive Nesterov Momentum Algorithm for Faster Optimizing Deep Models[J]. arXiv preprint arXiv:2208.06677, 2022. https://arxiv.org/abs/2208.06677 Implementation adapted from https://github.com/sail-sg/Adan """ import math import torch from torch.optim import Optimizer class Adan(Opt...
pytorch-image-models/timm/optim/adan.py/0
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""" MultiStep LR Scheduler Basic multi step LR schedule with warmup, noise. """ import torch import bisect from timm.scheduler.scheduler import Scheduler from typing import List class MultiStepLRScheduler(Scheduler): """ """ def __init__( self, optimizer: torch.optim.Optimizer, ...
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""" Logging helpers Hacked together by / Copyright 2020 Ross Wightman """ import logging import logging.handlers class FormatterNoInfo(logging.Formatter): def __init__(self, fmt='%(levelname)s: %(message)s'): logging.Formatter.__init__(self, fmt) def format(self, record): if record.levelno =...
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# Rust builder FROM lukemathwalker/cargo-chef:latest-rust-1.80 AS chef WORKDIR /usr/src ARG CARGO_REGISTRIES_CRATES_IO_PROTOCOL=sparse FROM chef AS planner COPY Cargo.lock Cargo.lock COPY Cargo.toml Cargo.toml COPY rust-toolchain.toml rust-toolchain.toml COPY proto proto COPY benchmark benchmark COPY router router CO...
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// // Created by Morgan Funtowicz on 6/30/24. // #ifndef TGI_TRTLLM_BACKEND_H #define TGI_TRTLLM_BACKEND_H #include <cmath> #include <filesystem> #include <span> #include <vector> #include <nlohmann/json.hpp> #include <tensorrt_llm/runtime/common.h> #include <tensorrt_llm/executor/executor.h> #include <tensorrt_llm...
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<html> <head> <!-- Load the latest Swagger UI code and style from npm using unpkg.com --> <script src="https://unpkg.com/swagger-ui-dist@3/swagger-ui-bundle.js"></script> <link rel="stylesheet" type="text/css" href="https://unpkg.com/swagger-ui-dist@3/swagger-ui.css"/> <title>Text Ge...
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# LoRA (Low-Rank Adaptation) ## What is LoRA? LoRA is a technique that allows for efficent fine-tuning a model while only updating a small portion of the model's weights. This is useful when you have a large model that has been pre-trained on a large dataset, but you want to fine-tune it on a smaller dataset or for a...
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# Text-generation-launcher arguments <!-- WRAP CODE BLOCKS --> ```shell Text Generation Launcher Usage: text-generation-launcher [OPTIONS] Options: ``` ## MODEL_ID ```shell --model-id <MODEL_ID> The name of the model to load. Can be a MODEL_ID as listed on <https://hf.co/models> like `gpt2` or `Open...
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[ { "choices": [ { "finish_reason": "", "index": 0, "logprobs": null, "text": "\n" } ], "created": 1724833943, "id": "", "model": "TinyLlama/TinyLlama-1.1B-Chat-v1.0", "object": "text_completion", "system_fingerprint": "2.2.1-dev0-native" }, ...
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{ "details": { "best_of_sequences": null, "finish_reason": "length", "generated_tokens": 10, "prefill": [ { "id": 2, "logprob": null, "text": "<bos>" }, { "id": 106, "logprob": -47.25, "text": "<start_of_turn>" }, { ...
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{ "details": { "best_of_sequences": null, "finish_reason": "length", "generated_tokens": 10, "prefill": [ { "id": 2323, "logprob": null, "text": "Test" }, { "id": 1715, "logprob": -11.453125, "text": " request" } ], "seed"...
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