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""" This script ports models from VQ-diffusion (https://github.com/microsoft/VQ-Diffusion) to diffusers. It currently only supports porting the ITHQ dataset. ITHQ dataset: ```sh # From the root directory of diffusers. # Download the VQVAE checkpoint $ wget https://facevcstandard.blob.core.windows.net/v-zhictang/Impr...
diffusers/scripts/convert_vq_diffusion_to_diffusers.py/0
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from .value_guided_sampling import ValueGuidedRLPipeline
diffusers/src/diffusers/experimental/rl/__init__.py/0
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# Models For more detail on the models, please refer to the [docs](https://huggingface.co/docs/diffusers/api/models/overview).
diffusers/src/diffusers/models/README.md/0
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# Copyright 2024 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
diffusers/src/diffusers/models/autoencoders/vq_model.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/models/modeling_pytorch_flax_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/transformers/t5_film_transformer.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_kandinsky3.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/blip_diffusion/modeling_blip2.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/controlnet/pipeline_flax_controlnet.py/0
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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 torch from transformers import CLIPImageProcessor, T5EncoderModel, T5Tokenizer from ...loaders import StableDiffusionLoraLoaderMixin from ...models import UNet2DConditionModel from ...sc...
diffusers/src/diffusers/pipelines/deepfloyd_if/pipeline_if.py/0
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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 # Copied from diffusers.pipelines.stable_diffusion.pipeline_output.StableDiffusionPipelineOutput with Stable->Alt class AltDiffusionPipelineOutput(BaseO...
diffusers/src/diffusers/pipelines/deprecated/alt_diffusion/pipeline_output.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/pipeline_spectrogram_diffusion.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/deprecated/vq_diffusion/__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/kandinsky/pipeline_kandinsky_combined.py/0
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from typing import Callable, Dict, List, Optional, Union import torch from transformers import T5EncoderModel, T5Tokenizer from ...loaders import StableDiffusionLoraLoaderMixin from ...models import Kandinsky3UNet, VQModel from ...schedulers import DDPMScheduler from ...utils import ( deprecate, logging, ...
diffusers/src/diffusers/pipelines/kandinsky3/pipeline_kandinsky3.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/pipelines/pipeline_flax_utils.py/0
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# Copyright 2024 Stability 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 requ...
diffusers/src/diffusers/pipelines/stable_audio/pipeline_stable_audio.py/0
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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, is_flax_available @dataclass class StableDiffusionPipelineOutput(BaseOutput): """ Output class for Stable Diffusion pipelines. Args: images (`List[PIL....
diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_output.py/0
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# Copyright 2024 Stability 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 requ...
diffusers/src/diffusers/pipelines/stable_diffusion_3/pipeline_stable_diffusion_3.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_video_diffusion/pipeline_stable_video_diffusion.py/0
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import math from typing import Optional, Union import torch from torch import nn from ...configuration_utils import ConfigMixin, register_to_config from ...models import ModelMixin from ...models.attention import FeedForward from ...models.attention_processor import Attention from ...models.embeddings import Timestep...
diffusers/src/diffusers/pipelines/unidiffuser/modeling_uvit.py/0
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import math from dataclasses import dataclass from typing import List, Optional, Tuple, Union import torch from ..configuration_utils import ConfigMixin, register_to_config from ..utils import BaseOutput from .scheduling_utils import SchedulerMixin def gumbel_noise(t, generator=None): device = generator.device ...
diffusers/src/diffusers/schedulers/scheduling_amused.py/0
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# Copyright 2024 TSAIL 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 requir...
diffusers/src/diffusers/schedulers/scheduling_dpmsolver_multistep_flax.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_lcm.py/0
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# 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 required by appl...
diffusers/src/diffusers/utils/__init__.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 AltDiffusionImg2ImgPipeline(metaclass=DummyObject): _backends = ["torch", "transformers"] def __init__(self, *args, **kwargs): requires_backends(self, ["torch", "transf...
diffusers/src/diffusers/utils/dummy_torch_and_transformers_objects.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/video_processor.py/0
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import unittest import torch from torch import nn from diffusers.models.activations import get_activation class ActivationsTests(unittest.TestCase): def test_swish(self): act = get_activation("swish") self.assertIsInstance(act, nn.SiLU) self.assertEqual(act(torch.tensor(-100, dtype=tor...
diffusers/tests/models/test_activations.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_temporal.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_ema.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_blip_diffusion.py/0
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# coding=utf-8 # Copyright 2023 HuggingFace Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or ag...
diffusers/tests/pipelines/controlnet_xs/test_controlnetxs_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/latent_diffusion/test_latent_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_controlnet_sd.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_cascade/test_stable_cascade_prior.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_flax_inpaint.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_image_variation/test_stable_diffusion_image_variation.py/0
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# coding=utf-8 # Copyright 2024 Harutatsu Akiyama and 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 b...
diffusers/tests/pipelines/stable_diffusion_xl/test_stable_diffusion_xl_instruction_pix2pix.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/text_to_video_synthesis/test_text_to_video_zero.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/single_file/test_model_vae_single_file.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/check_dummies.py/0
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# coding=utf-8 # Copyright 2021 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/tests_fetcher.py/0
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# Configure image ARG PYTHON_VERSION=3.10 FROM python:${PYTHON_VERSION}-slim ARG PYTHON_VERSION ARG DEBIAN_FRONTEND=noninteractive # Install apt dependencies RUN apt-get update && apt-get install -y --no-install-recommends \ build-essential cmake \ libglib2.0-0 libgl1-mesa-glx libegl1-mesa ffmpeg \ speech...
lerobot/docker/lerobot-cpu/Dockerfile/0
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#!/usr/bin/env python # Copyright 2024 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # ...
lerobot/lerobot/common/datasets/factory.py/0
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#!/usr/bin/env python # Copyright 2024 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # ...
lerobot/lerobot/common/datasets/push_dataset_to_hub/_umi_imagecodecs_numcodecs.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/video_utils.py/0
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#!/usr/bin/env python # Copyright 2024 Seungjae Lee and Yibin Wang and Haritheja Etukuru # and H. Jin Kim and Nur Muhammad Mahi Shafiullah and Lerrel Pinto # 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 com...
lerobot/lerobot/common/policies/vqbet/vqbet_utils.py/0
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# @package _global_ fps: 30 env: name: real_world task: null state_dim: 6 action_dim: 6 fps: ${fps}
lerobot/lerobot/configs/env/koch_real.yaml/0
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179
#!/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/scripts/eval.py/0
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180
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lerobot/tests/data/lerobot/aloha_sim_transfer_cube_human_image/train/data-00000-of-00001.arrow/0
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lerobot/tests/data/lerobot/aloha_static_battery/meta_data/episode_data_index.safetensors/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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{ "model_name_or_path": "./parler-tts-untrained-600M/parler-tts-untrained-600M/", "save_to_disk": "./tmp_dataset_audio/", "temporary_save_to_disk": "./audio_code_tmp/", "wandb_project": "parler-tts-50k-hours", "wandb_run_name": "Mini", "feature_extractor_name":"ylacombe/dac_44khZ_8kbps", "...
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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...
parler-tts/training/run_parler_tts_training.py/0
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# PEFT Docker images Here we store all PEFT Docker images used in our testing infrastructure. We use python 3.8 for now on all our images. - `peft-cpu`: PEFT compiled on CPU with all other HF libraries installed on main branch - `peft-gpu`: PEFT complied for NVIDIA GPUs wih all other HF libraries installed on main br...
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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...
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<!--⚠️ 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...
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<!--Copyright 2023 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
peft/docs/source/package_reference/prefix_tuning.md/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/boft_controlnet/test_controlnet.py/0
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#!/usr/bin/env python # 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 require...
peft/examples/boft_dreambooth/train_dreambooth.py/0
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import os import torch from datasets import load_dataset from torch.utils.data import DataLoader from tqdm import tqdm from transformers import AutoModelForSeq2SeqLM, AutoTokenizer, default_data_collator, get_linear_schedule_with_warmup from peft import AdaLoraConfig, PeftConfig, PeftModel, TaskType, get_peft_model ...
peft/examples/conditional_generation/peft_adalora_seq2seq.py/0
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<jupyter_start><jupyter_code>import argparse import json import logging import math import os import random from pathlib import Path from tqdm import tqdm import datasets from datasets import load_dataset, DatasetDict import evaluate import torch from torch import nn from torch.utils.data import DataLoader import tr...
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<jupyter_start><jupyter_text>Fine-tune FLAN-T5 using `bitsandbytes`, `peft` & `transformers` 🤗 In this notebook we will see how to properly use `peft` , `transformers` & `bitsandbytes` to fine-tune `flan-t5-large` in a google colab!We will finetune the model on [`financial_phrasebank`](https://huggingface.co/datasets...
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<jupyter_start><jupyter_code>import os os.environ["CUDA_VISIBLE_DEVICES"] = "1" from peft import PeftConfig, PeftModel from peft import PeftModel, PeftConfig from transformers import AutoModelForCausalLM, AutoTokenizer from datasets import load_dataset import torch import random peft_model_id = "smangrul/tinyllama_lo...
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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 import peft import evaluate from datasets import load_dataset from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed ...
peft/examples/sequence_classification/IA3.ipynb/0
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accelerate launch --config_file "configs/deepspeed_config.yaml" train.py \ --seed 100 \ --model_name_or_path "meta-llama/Llama-2-70b-hf" \ --dataset_name "smangrul/ultrachat-10k-chatml" \ --chat_template_format "chatml" \ --add_special_tokens False \ --append_concat_token False \ --splits "train,test" \ --max_seq_len ...
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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/scripts/launch_notebook_mp.py/0
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# Copyright (c) Meta Platforms, Inc. and affiliates. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. # Adapted from https://botorch.org/api/_modules/botorch/utils/torch.html # TODO: To be removed once (if) https://github.com/pytorch/pytorch...
peft/src/peft/tuners/_buffer_dict.py/0
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// Author: Yao Feng // Date: 2023/08 // Description: cuda kernel for fast block diag #include <ATen/ATen.h> #include <cuda.h> #include <cuda_runtime.h> #include <vector> namespace{ template <typename scalar_t> __global__ void forward_fast_block_diag_cuda_kernel( const scalar_t* __restrict__ input, //[z, N, b...
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# Copyright 2023-present the HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or...
peft/src/peft/tuners/lora/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/oft/layer.py/0
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# Copyright 2023-present the HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or...
peft/src/peft/tuners/tuners_utils.py/0
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# flake8: noqa # There's no way to ignore "F401 '...' imported but unused" warnings in this # module, but to preserve other warnings. So, don't check this module at all # coding=utf-8 # Copyright 2023-present the HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not u...
peft/src/peft/utils/peft_types.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/tests/test_hub_features.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/tests/testing_utils.py/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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# DenseNet **DenseNet** is a type of convolutional neural network that utilises dense connections between layers, through [Dense Blocks](http://www.paperswithcode.com/method/dense-block), where we connect *all layers* (with matching feature-map sizes) directly with each other. To preserve the feed-forward nature, each...
pytorch-image-models/hfdocs/source/models/densenet.mdx/0
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# Instagram ResNeXt WSL 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 transfo...
pytorch-image-models/hfdocs/source/models/ig-resnext.mdx/0
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# Res2Net **Res2Net** is an image model that employs a variation on bottleneck residual blocks, [Res2Net Blocks](https://paperswithcode.com/method/res2net-block). The motivation is to be able to represent features at multiple scales. This is achieved through a novel building block for CNNs that constructs hierarchical...
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# (Tensorflow) EfficientNet CondConv **EfficientNet** is a convolutional neural network architecture and scaling method that uniformly scales all dimensions of depth/width/resolution using a *compound coefficient*. Unlike conventional practice that arbitrary scales these factors, the EfficientNet scaling method unifo...
pytorch-image-models/hfdocs/source/models/tf-efficientnet-condconv.mdx/0
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dependencies = ['torch'] import timm globals().update(timm.models._registry._model_entrypoints)
pytorch-image-models/hubconf.py/0
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[dist_conda] conda_name_differences = 'torch:pytorch' channels = pytorch noarch = True [metadata] url = "https://github.com/huggingface/pytorch-image-models"
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from abc import ABC, abstractmethod from typing import Dict, List, Optional, Union class DatasetInfo(ABC): def __init__(self): pass @abstractmethod def num_classes(self): pass @abstractmethod def label_names(self): pass @abstractmethod def label_descriptions(sel...
pytorch-image-models/timm/data/dataset_info.py/0
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""" Dataset reader that wraps TFDS datasets Wraps many (most?) TFDS image-classification datasets from https://github.com/tensorflow/datasets https://www.tensorflow.org/datasets/catalog/overview#image_classification Hacked together by / Copyright 2020 Ross Wightman """ import math import os import sys from typing imp...
pytorch-image-models/timm/data/readers/reader_tfds.py/0
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""" CBAM (sort-of) Attention Experimental impl of CBAM: Convolutional Block Attention Module: https://arxiv.org/abs/1807.06521 WARNING: Results with these attention layers have been mixed. They can significantly reduce performance on some tasks, especially fine-grained it seems. I may end up removing this impl. Hack...
pytorch-image-models/timm/layers/cbam.py/0
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from enum import Enum from typing import Union import torch class Format(str, Enum): NCHW = 'NCHW' NHWC = 'NHWC' NCL = 'NCL' NLC = 'NLC' FormatT = Union[str, Format] def get_spatial_dim(fmt: FormatT): fmt = Format(fmt) if fmt is Format.NLC: dim = (1,) elif fmt is Format.NCL: ...
pytorch-image-models/timm/layers/format.py/0
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""" MLP module w/ dropout and configurable activation layer Hacked together by / Copyright 2020 Ross Wightman """ from functools import partial from torch import nn as nn from .grn import GlobalResponseNorm from .helpers import to_2tuple class Mlp(nn.Module): """ MLP as used in Vision Transformer, MLP-Mixer an...
pytorch-image-models/timm/layers/mlp.py/0
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""" Squeeze-and-Excitation Channel Attention An SE implementation originally based on PyTorch SE-Net impl. Has since evolved with additional functionality / configuration. Paper: `Squeeze-and-Excitation Networks` - https://arxiv.org/abs/1709.01507 Also included is Effective Squeeze-Excitation (ESE). Paper: `CenterMa...
pytorch-image-models/timm/layers/squeeze_excite.py/0
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""" PyTorch Feature Extraction Helpers A collection of classes, functions, modules to help extract features from models and provide a common interface for describing them. The return_layers, module re-writing idea inspired by torchvision IntermediateLayerGetter https://github.com/pytorch/vision/blob/d88d8961ae51507d0...
pytorch-image-models/timm/models/_features.py/0
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""" Class-Attention in Image Transformers (CaiT) Paper: 'Going deeper with Image Transformers' - https://arxiv.org/abs/2103.17239 Original code and weights from https://github.com/facebookresearch/deit, copyright below Modifications and additions for timm hacked together by / Copyright 2021, Ross Wightman """ # Copy...
pytorch-image-models/timm/models/cait.py/0
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""" EfficientViT (by MIT Song Han's Lab) Paper: `Efficientvit: Enhanced linear attention for high-resolution low-computation visual recognition` - https://arxiv.org/abs/2205.14756 Adapted from official impl at https://github.com/mit-han-lab/efficientvit """ __all__ = ['EfficientVit', 'EfficientVitLarge'] from ty...
pytorch-image-models/timm/models/efficientvit_mit.py/0
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""" Normalization Free Nets. NFNet, NF-RegNet, NF-ResNet (pre-activation) Models Paper: `Characterizing signal propagation to close the performance gap in unnormalized ResNets` - https://arxiv.org/abs/2101.08692 Paper: `High-Performance Large-Scale Image Recognition Without Normalization` - https://arxiv.org/...
pytorch-image-models/timm/models/nfnet.py/0
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