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# Copyright 2025 Alibaba DAMO-VILAB and The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unles...
diffusers/src/diffusers/models/unets/unet_i2vgen_xl.py/0
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151
# Copyright 2025 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/modular_pipelines/flux/modular_blocks.py/0
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# Copyright 2025 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/modular_pipelines/wan/encoders.py/0
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153
# Copyright 2025 Salesforce.com, inc. # Copyright 2025 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/LICENS...
diffusers/src/diffusers/pipelines/blip_diffusion/modeling_ctx_clip.py/0
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# Copyright 2025 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_xs/pipeline_controlnet_xs_sd_xl.py/0
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# Copyright 2025 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
diffusers/src/diffusers/pipelines/deprecated/audio_diffusion/mel.py/0
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# Copyright 2025 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
diffusers/src/diffusers/pipelines/deprecated/stable_diffusion_variants/pipeline_cycle_diffusion.py/0
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from typing import TYPE_CHECKING from ...utils import DIFFUSERS_SLOW_IMPORT, _LazyModule _import_structure = {"pipeline_dit": ["DiTPipeline"]} if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT: from .pipeline_dit import DiTPipeline else: import sys sys.modules[__name__] = _LazyModule( __name__, ...
diffusers/src/diffusers/pipelines/dit/__init__.py/0
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# Copyright 2025 The HunyuanVideo 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 # # Un...
diffusers/src/diffusers/pipelines/hunyuan_video/pipeline_hunyuan_video_image2video.py/0
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# Copyright 2025 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_controlnet.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 i...
diffusers/src/diffusers/pipelines/pixart_alpha/__init__.py/0
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# Copyright 2025 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/modeling_stable_audio.py/0
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162
# Copyright 2025 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_onnx_stable_diffusion_upscale.py/0
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from typing import TYPE_CHECKING from ...utils import ( DIFFUSERS_SLOW_IMPORT, BaseOutput, OptionalDependencyNotAvailable, _LazyModule, get_objects_from_module, is_torch_available, is_transformers_available, ) _dummy_objects = {} _import_structure = {} try: if not (is_transformers_av...
diffusers/src/diffusers/pipelines/stable_video_diffusion/__init__.py/0
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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/unidiffuser/__init__.py/0
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import torch import torch.nn as nn from ...models.attention_processor import Attention class WuerstchenLayerNorm(nn.LayerNorm): def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) def forward(self, x): x = x.permute(0, 2, 3, 1) x = super().forward(x) return...
diffusers/src/diffusers/pipelines/wuerstchen/modeling_wuerstchen_common.py/0
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# Copyright 2025 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/quantizers/pipe_quant_config.py/0
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# Copyright 2025 Zhejiang University Team and The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # #...
diffusers/src/diffusers/schedulers/scheduling_pndm.py/0
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# 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/LICENSE-2.0 # # Unless required by appl...
diffusers/src/diffusers/utils/constants.py/0
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169
# This file is autogenerated by the command `make fix-copies`, do not edit. from ..utils import DummyObject, requires_backends class ConsisIDPipeline(metaclass=DummyObject): _backends = ["torch", "transformers", "opencv"] def __init__(self, *args, **kwargs): requires_backends(self, ["torch", "transfo...
diffusers/src/diffusers/utils/dummy_torch_and_transformers_and_opencv_objects.py/0
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import ast import importlib import inspect import textwrap class ReturnNameVisitor(ast.NodeVisitor): """Thanks to ChatGPT for pairing.""" def __init__(self): self.return_names = [] def visit_Return(self, node): # Check if the return value is a tuple. if isinstance(node.value, ast...
diffusers/src/diffusers/utils/source_code_parsing_utils.py/0
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# Copyright 2025 HuggingFace Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writ...
diffusers/tests/lora/test_lora_layers_cogview4.py/0
{ "file_path": "diffusers/tests/lora/test_lora_layers_cogview4.py", "repo_id": "diffusers", "token_count": 2870 }
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# coding=utf-8 # Copyright 2025 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_asymmetric_autoencoder_kl.py/0
{ "file_path": "diffusers/tests/models/autoencoders/test_models_asymmetric_autoencoder_kl.py", "repo_id": "diffusers", "token_count": 4817 }
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def get_autoencoder_kl_config(block_out_channels=None, norm_num_groups=None): block_out_channels = block_out_channels or [2, 4] norm_num_groups = norm_num_groups or 2 init_dict = { "block_out_channels": block_out_channels, "in_channels": 3, "out_channels": 3, "down_block_type...
diffusers/tests/models/autoencoders/vae.py/0
{ "file_path": "diffusers/tests/models/autoencoders/vae.py", "repo_id": "diffusers", "token_count": 1582 }
174
# coding=utf-8 # Copyright 2025 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_qwenimage.py/0
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# coding=utf-8 # Copyright 2025 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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# coding=utf-8 # Copyright 2025 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_video_processor.py/0
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177
# Copyright 2024 Bria 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/tests/pipelines/bria/test_pipeline_bria.py/0
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import gc import unittest import numpy as np import torch from torch.backends.cuda import sdp_kernel from diffusers import ( CMStochasticIterativeScheduler, ConsistencyModelPipeline, UNet2DModel, ) from diffusers.utils.testing_utils import ( Expectations, backend_empty_cache, enable_full_deter...
diffusers/tests/pipelines/consistency_models/test_consistency_models.py/0
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# coding=utf-8 # Copyright 2025 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_sd3/test_controlnet_inpaint_sd3.py/0
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180
# coding=utf-8 # Copyright 2025 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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# Copyright 2025 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/ltx/test_ltx_latent_upsample.py/0
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# coding=utf-8 # Copyright 2025 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_inpaint.py/0
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# coding=utf-8 # Copyright 2025 HuggingFace Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or ag...
diffusers/tests/pipelines/stable_diffusion/test_onnx_stable_diffusion.py/0
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# coding=utf-8 # Copyright 2025 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_v_pred.py/0
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import gc import unittest import torch from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer from diffusers import ( AutoencoderKL, DDIMScheduler, DDPMScheduler, PriorTransformer, StableUnCLIPPipeline, UNet2DConditionModel, ) from diffusers.pipeline...
diffusers/tests/pipelines/stable_unclip/test_stable_unclip.py/0
{ "file_path": "diffusers/tests/pipelines/stable_unclip/test_stable_unclip.py", "repo_id": "diffusers", "token_count": 4177 }
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# Copyright 2025 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/wan/test_wan_22.py/0
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187
The tests here are adapted from [`transformers` tests](https://github.com/huggingface/transformers/blob/3a8eb74668e9c2cc563b2f5c62fac174797063e0/tests/quantization/torchao_integration/). The benchmarks were run on a single H100. Below is `nvidia-smi`: ```bash +---------------------------------------------------------...
diffusers/tests/quantization/torchao/README.md/0
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import tempfile import torch from diffusers import DPMSolverMultistepInverseScheduler, DPMSolverMultistepScheduler from .test_schedulers import SchedulerCommonTest class DPMSolverMultistepSchedulerTest(SchedulerCommonTest): scheduler_classes = (DPMSolverMultistepInverseScheduler,) forward_default_kwargs = ...
diffusers/tests/schedulers/test_scheduler_dpm_multi_inverse.py/0
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import tempfile import unittest import numpy as np import torch from diffusers import ScoreSdeVeScheduler class ScoreSdeVeSchedulerTest(unittest.TestCase): # TODO adapt with class SchedulerCommonTest (scheduler needs Numpy Integration) scheduler_classes = (ScoreSdeVeScheduler,) forward_default_kwargs = ...
diffusers/tests/schedulers/test_scheduler_score_sde_ve.py/0
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# coding=utf-8 # Copyright 2025 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_wan_transformer3d_single_file.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/utils/check_doc_toc.py/0
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192
# 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/utils/overwrite_expected_slice.py/0
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193
# HIL-SERL Real Robot Training Workflow Guide In this tutorial you will go through the full Human-in-the-Loop Sample-Efficient Reinforcement Learning (HIL-SERL) workflow using LeRobot. You will master training a policy with RL on a real robot in just a few hours. HIL-SERL is a sample-efficient reinforcement learning ...
lerobot/docs/source/hilserl.mdx/0
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# Finetune SmolVLA SmolVLA is Hugging Face’s lightweight foundation model for robotics. Designed for easy fine-tuning on LeRobot datasets, it helps accelerate your development! <p align="center"> <img src="https://cdn-uploads.huggingface.co/production/uploads/640e21ef3c82bd463ee5a76d/aooU0a3DMtYmy_1IWMaIM.png" ...
lerobot/docs/source/smolvla.mdx/0
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195
#!/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/src/lerobot/cameras/configs.py/0
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--- # For reference on dataset card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/datasetcard.md?plain=1 # Doc / guide: https://huggingface.co/docs/hub/datasets-cards # prettier-ignore {{card_data}} --- This dataset was created using [LeRobot](https://github.com/huggingface/lerobot). ## Da...
lerobot/src/lerobot/datasets/card_template.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/src/lerobot/datasets/video_utils.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...
lerobot/src/lerobot/motors/feetech/tables.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...
lerobot/src/lerobot/policies/pi0/conversion_scripts/benchmark.py/0
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#!/usr/bin/env python # Copyright 2025 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 # # Unle...
lerobot/src/lerobot/policies/smolvla/modeling_smolvla.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...
lerobot/src/lerobot/record.py/0
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This tutorial explains how to use [Stretch 3](https://hello-robot.com/stretch-3-product) with LeRobot. ## Setup Familiarize yourself with Stretch by following its [tutorials](https://docs.hello-robot.com/0.3/getting_started/hello_robot/) (recommended). To use LeRobot on Stretch, 3 options are available: - [tethered...
lerobot/src/lerobot/robots/stretch3/README.md/0
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# !/usr/bin/env python # 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/LICENSE-2.0 #...
lerobot/src/lerobot/scripts/rl/learner.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/src/lerobot/teleoperators/koch_leader/koch_leader.py/0
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<!DOCTYPE html> <html lang="en"> <head> <meta charset="UTF-8"> <meta name="viewport" content="width=device-width, initial-scale=1.0"> <title>Interactive Video Background Page</title> <script src="https://cdn.tailwindcss.com"></script> <script defer src="https://cdn.jsdelivr.net/npm/alpinejs@3.x.x/di...
lerobot/src/lerobot/templates/visualize_dataset_homepage.html/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/src/lerobot/utils/random_utils.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/datasets/test_compute_stats.py/0
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#!/usr/bin/env python # 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/LICENSE-2.0 # # ...
lerobot/tests/mocks/mock_dynamixel.py/0
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#!/usr/bin/env python # 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/LICENSE-2.0 # # ...
lerobot/tests/processor/test_normalize_processor.py/0
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#!/usr/bin/env python # 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/LICENSE-2.0 # # ...
lerobot/tests/utils/test_queue.py/0
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# Post-training recipes ## OpenR1 Distill 7B To train the OpenR1 Distill 7B model, run: ``` sbatch --nodes=1 slurm/train.slurm --model OpenR1-Distill-7B --task sft --config distill --accelerator zero3 ``` ## OlympicCoder To train the OlympicCoder models, run: ``` # 7B sbatch --nodes=1 slurm/train.slurm --model Ol...
open-r1/recipes/README.md/0
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# a bash foor loop from 0 to 17,400 in chunks of 200 for i in {0..17000..200} do START=$i END=$((i + 200)) echo "Processing chunk from $START to $END" # Submit the job to SLURM sbatch slurm/compute_pass_rate.slurm recipes/dataset_filtering/filter_dapo.yaml $START $END done sbatch slurm/compute_pass_rat...
open-r1/scripts/pass_rate_filtering/launch_filtering.sh/0
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#!/bin/bash #SBATCH --job-name=r1-router #SBATCH --partition=hopper-cpu #SBATCH --qos=high #SBATCH --nodes=1 #SBATCH --cpus-per-task=8 #SBATCH --mem-per-cpu=1875m #SBATCH --output=./logs/%x_%j_%n.out #SBATCH --error=./logs/%x_%j_%n.err #SBATCH --time=30-00:00:00 #SBATCH --requeue set -exuo pipefail # TODO: Adjust the...
open-r1/slurm/serve_router.slurm/0
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import asyncio import json import logging import os import tempfile from typing import Any, Dict, Optional, Tuple from dotenv import load_dotenv from open_r1.utils.import_utils import is_morph_available # Replace direct imports with conditional imports if is_morph_available(): from morphcloud.api import Instance...
open-r1/src/open_r1/utils/competitive_programming/morph_client.py/0
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.PHONY: quality style test docs check_dirs := src tests examples docs scripts docker # Check that source code meets quality standards # this target runs checks on all files quality: ruff check $(check_dirs) ruff format --check $(check_dirs) doc-builder style src/peft tests docs/source --max_len 119 --check_only ...
peft/Makefile/0
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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. --> # Soft prompts Training large pretrained language models is very time-consuming and compute-intensive. As they continue to grow in size, there is in...
peft/docs/source/conceptual_guides/prompting.md/0
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import gc import os import sys import threading import psutil import torch from accelerate import Accelerator from datasets import load_dataset from torch.utils.data import DataLoader from tqdm import tqdm from transformers import AutoModelForSeq2SeqLM, AutoTokenizer, get_linear_schedule_with_warmup, set_seed from pe...
peft/examples/conditional_generation/peft_lora_seq2seq_accelerate_ds_zero3_offload.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/examples/ephemeral_gpu_offloading/load_with_dora.py/0
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# LoftQ: LoRA-fine-tuning-aware Quantization ## Introduction LoftQ finds quantized LoRA initialization: quantized backbone Q and LoRA adapters A and B, given a pre-trained weight W. ## Quick Start Steps: 1. Apply LoftQ to a full-precision pre-trained weight and save. 2. Load LoftQ initialization and train. For ste...
peft/examples/loftq_finetuning/README.md/0
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# Supervised Fine-tuning (SFT) with PEFT In this example, we'll see how to use [PEFT](https://github.com/huggingface/peft) to perform SFT using PEFT on various distributed setups. ## Single GPU SFT with QLoRA QLoRA uses 4-bit quantization of the base model to drastically reduce the GPU memory consumed by the base mode...
peft/examples/sft/README.md/0
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import os import sys from dataclasses import dataclass, field from typing import Optional from transformers import HfArgumentParser, set_seed from trl import SFTConfig, SFTTrainer from utils import create_and_prepare_model, create_datasets # Define and parse arguments. @dataclass class ModelArguments: """ Ar...
peft/examples/sft/train.py/0
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{ "model_id": "meta-llama/Llama-3.2-3B", "dtype": "bfloat16", "max_seq_length": 768, "batch_size": 4, "batch_size_eval": 50, "max_steps": 5000, "eval_steps": 250, "compile": false, "seed": 0, "grad_norm_clip": 1.0, "optimizer_type": "AdamW", "optimizer_kwargs": { "lr": 1e-4, "weight_deca...
peft/method_comparison/MetaMathQA/default_training_params.json/0
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{ "alpha": 64, "alpha_pattern": {}, "auto_mapping": null, "base_model_name_or_path": null, "exclude_modules": null, "inference_mode": false, "init_weights": true, "layers_pattern": null, "layers_to_transform": null, "module_dropout": 0.0, "modules_to_save": null, "peft_type": "LOHA", "r": 32, ...
peft/method_comparison/MetaMathQA/experiments/loha/llama-3.2-3B-rank32/adapter_config.json/0
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{ "auto_mapping": null, "base_model_name_or_path": null, "group_size": 64, "inference_mode": false, "init_weights": true, "peft_type": "ROAD", "revision": null, "target_modules": null, "task_type": null, "variant": "road_2" }
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import ast import pandas as pd def _evaluate_node(df, node): """ Recursively evaluates an AST node to generate a pandas boolean mask. """ # Base Case: A simple comparison like 'price > 100' if isinstance(node, ast.Compare): if not isinstance(node.left, ast.Name): raise ValueEr...
peft/method_comparison/sanitizer.py/0
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#!/usr/bin/env python3 # Copyright (c) 2025 Your Organization/Project. 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 ...
peft/scripts/convert-bone-to-miss.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/optimizers/loraplus.py/0
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# Copyright 2023-present the HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or...
peft/src/peft/tuners/lora/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 2025-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/trainable_tokens/config.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/xlora/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/tests/test_hub_features.py/0
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# Copyright 2025-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_shira.py/0
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#!/bin/bash NUM_PROC=$1 shift torchrun --nproc_per_node=$NUM_PROC train.py "$@"
pytorch-image-models/distributed_train.sh/0
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# Deep Layer Aggregation Extending “shallow” skip connections, **Dense Layer Aggregation (DLA)** incorporates more depth and sharing. The authors introduce two structures for deep layer aggregation (DLA): iterative deep aggregation (IDA) and hierarchical deep aggregation (HDA). These structures are expressed through ...
pytorch-image-models/hfdocs/source/models/dla.mdx/0
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# Inception ResNet v2 **Inception-ResNet-v2** is a convolutional neural architecture that builds on the Inception family of architectures but incorporates [residual connections](https://paperswithcode.com/method/residual-connection) (replacing the filter concatenation stage of the Inception architecture). ## How do I...
pytorch-image-models/hfdocs/source/models/inception-resnet-v2.mdx/0
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# Res2NeXt **Res2NeXt** is an image model that employs a variation on [ResNeXt](https://paperswithcode.com/method/resnext) bottleneck residual blocks. 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 residual-li...
pytorch-image-models/hfdocs/source/models/res2next.mdx/0
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# (Tensorflow) EfficientNet Lite **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 uniformly ...
pytorch-image-models/hfdocs/source/models/tf-efficientnet-lite.mdx/0
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#!/usr/bin/env python3 """PyTorch Inference Script An example inference script that outputs top-k class ids for images in a folder into a csv. Hacked together by / Copyright 2020 Ross Wightman (https://github.com/rwightman) """ import argparse import json import logging import os import time from contextlib import su...
pytorch-image-models/inference.py/0
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""" Dataset Factory Hacked together by / Copyright 2021, Ross Wightman """ import os from typing import Optional from torchvision.datasets import CIFAR100, CIFAR10, MNIST, KMNIST, FashionMNIST, ImageFolder try: from torchvision.datasets import Places365 has_places365 = True except ImportError: has_places3...
pytorch-image-models/timm/data/dataset_factory.py/0
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import os from typing import Optional from .reader_image_folder import ReaderImageFolder from .reader_image_in_tar import ReaderImageInTar def create_reader( name: str, root: Optional[str] = None, split: str = 'train', **kwargs, ): kwargs = {k: v for k, v in kwargs.items() if v is...
pytorch-image-models/timm/data/readers/reader_factory.py/0
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""" Activations (memory-efficient w/ custom autograd) A collection of activations fn and modules with a common interface so that they can easily be swapped. All have an `inplace` arg even if not used. These activations are not compatible with jit scripting or ONNX export of the model, please use basic versions of the...
pytorch-image-models/timm/layers/activations_me.py/0
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""" Create Conv2d Factory Method Hacked together by / Copyright 2020 Ross Wightman """ from .mixed_conv2d import MixedConv2d from .cond_conv2d import CondConv2d from .conv2d_same import create_conv2d_pad def create_conv2d(in_channels, out_channels, kernel_size, **kwargs): """ Select a 2d convolution implementat...
pytorch-image-models/timm/layers/create_conv2d.py/0
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import torch from torch import nn as nn try: from inplace_abn.functions import inplace_abn, inplace_abn_sync has_iabn = True except ImportError: has_iabn = False def inplace_abn(x, weight, bias, running_mean, running_var, training=True, momentum=0.1, eps=1e-05, activation="leaky_re...
pytorch-image-models/timm/layers/inplace_abn.py/0
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""" AvgPool2d w/ Same Padding Hacked together by / Copyright 2020 Ross Wightman """ import torch import torch.nn as nn import torch.nn.functional as F from typing import List, Tuple, Optional from ._fx import register_notrace_module from .helpers import to_2tuple from .padding import pad_same, get_padding_value def...
pytorch-image-models/timm/layers/pool2d_same.py/0
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import torch import torch.nn as nn class AsymmetricLossMultiLabel(nn.Module): def __init__(self, gamma_neg=4, gamma_pos=1, clip=0.05, eps=1e-8, disable_torch_grad_focal_loss=False): super(AsymmetricLossMultiLabel, self).__init__() self.gamma_neg = gamma_neg self.gamma_pos = gamma_pos ...
pytorch-image-models/timm/loss/asymmetric_loss.py/0
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""" DaViT: Dual Attention Vision Transformers As described in https://arxiv.org/abs/2204.03645 Input size invariant transformer architecture that combines channel and spacial attention in each block. The attention mechanisms used are linear in complexity. DaViT model defs and weights adapted from https://github.com/...
pytorch-image-models/timm/models/davit.py/0
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""" FocalNet As described in `Focal Modulation Networks` - https://arxiv.org/abs/2203.11926 Significant modifications and refactoring from the original impl at https://github.com/microsoft/FocalNet This impl is/has: * fully convolutional, NCHW tensor layout throughout, seemed to have minimal performance impact but m...
pytorch-image-models/timm/models/focalnet.py/0
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""" LeViT Paper: `LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference` - https://arxiv.org/abs/2104.01136 @article{graham2021levit, title={LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference}, author={Benjamin Graham and Alaaeldin El-Nouby and Hugo Touvron and Pierre Stoc...
pytorch-image-models/timm/models/levit.py/0
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