repo stringlengths 7 90 | file_url stringlengths 81 315 | file_path stringlengths 4 228 | content stringlengths 0 32.8k | language stringclasses 1
value | license stringclasses 7
values | commit_sha stringlengths 40 40 | retrieved_at stringdate 2026-01-04 14:38:15 2026-01-05 02:33:18 | truncated bool 2
classes |
|---|---|---|---|---|---|---|---|---|
commaai/openpilot | https://github.com/commaai/openpilot/blob/adbf68f77120b4568de68c37b8bed4ed433e01fe/selfdrive/debug/__init__.py | selfdrive/debug/__init__.py | python | MIT | adbf68f77120b4568de68c37b8bed4ed433e01fe | 2026-01-04T14:38:40.093933Z | false | |
commaai/openpilot | https://github.com/commaai/openpilot/blob/adbf68f77120b4568de68c37b8bed4ed433e01fe/selfdrive/debug/set_car_params.py | selfdrive/debug/set_car_params.py | #!/usr/bin/env python3
import sys
from cereal import car
from openpilot.common.params import Params
from openpilot.tools.lib.route import Route
from openpilot.tools.lib.logreader import LogReader
if __name__ == "__main__":
CP = None
if len(sys.argv) > 1:
r = Route(sys.argv[1])
cps = [m for m in LogReader(... | python | MIT | adbf68f77120b4568de68c37b8bed4ed433e01fe | 2026-01-04T14:38:40.093933Z | false |
commaai/openpilot | https://github.com/commaai/openpilot/blob/adbf68f77120b4568de68c37b8bed4ed433e01fe/selfdrive/debug/max_lat_accel.py | selfdrive/debug/max_lat_accel.py | #!/usr/bin/env python3
import argparse
import numpy as np
import matplotlib.pyplot as plt
from functools import partial
from tqdm import tqdm
from typing import NamedTuple
from openpilot.tools.lib.logreader import LogReader
from openpilot.selfdrive.locationd.models.pose_kf import EARTH_G
RLOG_MIN_LAT_ACTIVE = 50
RLOG_... | python | MIT | adbf68f77120b4568de68c37b8bed4ed433e01fe | 2026-01-04T14:38:40.093933Z | false |
commaai/openpilot | https://github.com/commaai/openpilot/blob/adbf68f77120b4568de68c37b8bed4ed433e01fe/selfdrive/debug/touch_replay.py | selfdrive/debug/touch_replay.py | #!/usr/bin/env python3
import argparse
import numpy as np
import matplotlib.pyplot as plt
from openpilot.tools.lib.logreader import LogReader
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--width', default=2160, type=int)
parser.add_argument('--height', default=1080, type=i... | python | MIT | adbf68f77120b4568de68c37b8bed4ed433e01fe | 2026-01-04T14:38:40.093933Z | false |
commaai/openpilot | https://github.com/commaai/openpilot/blob/adbf68f77120b4568de68c37b8bed4ed433e01fe/selfdrive/debug/check_can_parser_performance.py | selfdrive/debug/check_can_parser_performance.py | #!/usr/bin/env python3
import numpy as np
import time
from tqdm import tqdm
from cereal import car
from opendbc.car.tests.routes import CarTestRoute
from openpilot.selfdrive.car.tests.test_models import TestCarModelBase
from openpilot.tools.plotjuggler.juggle import DEMO_ROUTE
N_RUNS = 10
class CarModelTestCase(Tes... | python | MIT | adbf68f77120b4568de68c37b8bed4ed433e01fe | 2026-01-04T14:38:40.093933Z | false |
commaai/openpilot | https://github.com/commaai/openpilot/blob/adbf68f77120b4568de68c37b8bed4ed433e01fe/selfdrive/debug/cycle_alerts.py | selfdrive/debug/cycle_alerts.py | #!/usr/bin/env python3
import time
import random
from cereal import car, log
import cereal.messaging as messaging
from opendbc.car.honda.interface import CarInterface
from openpilot.common.realtime import DT_CTRL
from openpilot.selfdrive.selfdrived.events import ET, Events
from openpilot.selfdrive.selfdrived.alertmana... | python | MIT | adbf68f77120b4568de68c37b8bed4ed433e01fe | 2026-01-04T14:38:40.093933Z | false |
commaai/openpilot | https://github.com/commaai/openpilot/blob/adbf68f77120b4568de68c37b8bed4ed433e01fe/selfdrive/debug/can_printer.py | selfdrive/debug/can_printer.py | #!/usr/bin/env python3
import argparse
import binascii
import time
from collections import defaultdict
import cereal.messaging as messaging
def can_printer(bus, max_msg, addr, ascii_decode):
logcan = messaging.sub_sock('can', addr=addr)
start = time.monotonic()
lp = time.monotonic()
msgs = defaultdict(list)... | python | MIT | adbf68f77120b4568de68c37b8bed4ed433e01fe | 2026-01-04T14:38:40.093933Z | false |
commaai/openpilot | https://github.com/commaai/openpilot/blob/adbf68f77120b4568de68c37b8bed4ed433e01fe/selfdrive/debug/check_timings.py | selfdrive/debug/check_timings.py | #!/usr/bin/env python3
import sys
import time
import numpy as np
import datetime
from collections.abc import MutableSequence
from collections import defaultdict
import cereal.messaging as messaging
if __name__ == "__main__":
ts: defaultdict[str, MutableSequence[float]] = defaultdict(list)
socks = {s: messaging.s... | python | MIT | adbf68f77120b4568de68c37b8bed4ed433e01fe | 2026-01-04T14:38:40.093933Z | false |
commaai/openpilot | https://github.com/commaai/openpilot/blob/adbf68f77120b4568de68c37b8bed4ed433e01fe/selfdrive/debug/car/ecu_addrs.py | selfdrive/debug/car/ecu_addrs.py | #!/usr/bin/env python3
import argparse
import time
import cereal.messaging as messaging
from opendbc.car.carlog import carlog
from opendbc.car.ecu_addrs import get_all_ecu_addrs
from openpilot.common.params import Params
from openpilot.selfdrive.car.card import can_comm_callbacks, obd_callback
if __name__ == "__main_... | python | MIT | adbf68f77120b4568de68c37b8bed4ed433e01fe | 2026-01-04T14:38:40.093933Z | false |
commaai/openpilot | https://github.com/commaai/openpilot/blob/adbf68f77120b4568de68c37b8bed4ed433e01fe/selfdrive/debug/car/vw_mqb_config.py | selfdrive/debug/car/vw_mqb_config.py | #!/usr/bin/env python3
import argparse
import struct
from enum import IntEnum
from opendbc.car.carlog import carlog
from opendbc.car.uds import UdsClient, MessageTimeoutError, NegativeResponseError, SESSION_TYPE,\
DATA_IDENTIFIER_TYPE, ACCESS_TYPE
from opendbc.car.structs import CarParams
from panda import Panda
fro... | python | MIT | adbf68f77120b4568de68c37b8bed4ed433e01fe | 2026-01-04T14:38:40.093933Z | false |
commaai/openpilot | https://github.com/commaai/openpilot/blob/adbf68f77120b4568de68c37b8bed4ed433e01fe/selfdrive/debug/car/vin.py | selfdrive/debug/car/vin.py | #!/usr/bin/env python3
import argparse
import time
import cereal.messaging as messaging
from opendbc.car.carlog import carlog
from opendbc.car.vin import get_vin
from openpilot.selfdrive.car.card import can_comm_callbacks
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Get VIN of the car')
... | python | MIT | adbf68f77120b4568de68c37b8bed4ed433e01fe | 2026-01-04T14:38:40.093933Z | false |
commaai/openpilot | https://github.com/commaai/openpilot/blob/adbf68f77120b4568de68c37b8bed4ed433e01fe/selfdrive/debug/car/toyota_eps_factor.py | selfdrive/debug/car/toyota_eps_factor.py | #!/usr/bin/env python3
import sys
import numpy as np
import matplotlib.pyplot as plt
from sklearn import linear_model
from opendbc.car.toyota.values import STEER_THRESHOLD
from openpilot.tools.lib.logreader import LogReader
MIN_SAMPLES = 30 * 100
def to_signed(n, bits):
if n >= (1 << max((bits - 1), 0)):
n = ... | python | MIT | adbf68f77120b4568de68c37b8bed4ed433e01fe | 2026-01-04T14:38:40.093933Z | false |
commaai/openpilot | https://github.com/commaai/openpilot/blob/adbf68f77120b4568de68c37b8bed4ed433e01fe/selfdrive/debug/car/fw_versions.py | selfdrive/debug/car/fw_versions.py | #!/usr/bin/env python3
import time
import argparse
import cereal.messaging as messaging
from cereal import car
from opendbc.car.carlog import carlog
from opendbc.car.fw_versions import get_fw_versions, match_fw_to_car
from opendbc.car.vin import get_vin
from openpilot.common.params import Params
from openpilot.selfdriv... | python | MIT | adbf68f77120b4568de68c37b8bed4ed433e01fe | 2026-01-04T14:38:40.093933Z | false |
commaai/openpilot | https://github.com/commaai/openpilot/blob/adbf68f77120b4568de68c37b8bed4ed433e01fe/selfdrive/debug/car/clear_dtc.py | selfdrive/debug/car/clear_dtc.py | #!/usr/bin/env python3
import sys
import argparse
from subprocess import check_output, CalledProcessError
from opendbc.car.carlog import carlog
from opendbc.car.uds import UdsClient, MessageTimeoutError, SESSION_TYPE, DTC_GROUP_TYPE
from opendbc.car.structs import CarParams
from panda import Panda
parser = argparse.Ar... | python | MIT | adbf68f77120b4568de68c37b8bed4ed433e01fe | 2026-01-04T14:38:40.093933Z | false |
commaai/openpilot | https://github.com/commaai/openpilot/blob/adbf68f77120b4568de68c37b8bed4ed433e01fe/selfdrive/debug/car/disable_ecu.py | selfdrive/debug/car/disable_ecu.py | #!/usr/bin/env python3
import time
import cereal.messaging as messaging
from opendbc.car.disable_ecu import disable_ecu
from openpilot.selfdrive.car.card import can_comm_callbacks
if __name__ == "__main__":
sendcan = messaging.pub_sock('sendcan')
logcan = messaging.sub_sock('can')
can_callbacks = can_comm_callba... | python | MIT | adbf68f77120b4568de68c37b8bed4ed433e01fe | 2026-01-04T14:38:40.093933Z | false |
commaai/openpilot | https://github.com/commaai/openpilot/blob/adbf68f77120b4568de68c37b8bed4ed433e01fe/selfdrive/debug/car/hyundai_enable_radar_points.py | selfdrive/debug/car/hyundai_enable_radar_points.py | #!/usr/bin/env python3
"""Some Hyundai radars can be reconfigured to output (debug) radar points on bus 1.
Reconfiguration is done over UDS by reading/writing to 0x0142 using the Read/Write Data By Identifier
endpoints (0x22 & 0x2E). This script checks your radar firmware version against a list of known
firmware versio... | python | MIT | adbf68f77120b4568de68c37b8bed4ed433e01fe | 2026-01-04T14:38:40.093933Z | false |
commaai/openpilot | https://github.com/commaai/openpilot/blob/adbf68f77120b4568de68c37b8bed4ed433e01fe/docs/hooks/glossary.py | docs/hooks/glossary.py | import re
import tomllib
def load_glossary(file_path="docs/glossary.toml"):
with open(file_path, "rb") as f:
glossary_data = tomllib.load(f)
return glossary_data.get("glossary", {})
def generate_anchor_id(name):
return name.replace(" ", "-").replace("_", "-").lower()
def format_markdown_term(name, definiti... | python | MIT | adbf68f77120b4568de68c37b8bed4ed433e01fe | 2026-01-04T14:38:40.093933Z | false |
commaai/openpilot | https://github.com/commaai/openpilot/blob/adbf68f77120b4568de68c37b8bed4ed433e01fe/openpilot/__init__.py | openpilot/__init__.py | python | MIT | adbf68f77120b4568de68c37b8bed4ed433e01fe | 2026-01-04T14:38:40.093933Z | false | |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/setup.py | setup.py | # 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... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_omnigen_to_diffusers.py | scripts/convert_omnigen_to_diffusers.py | import argparse
import os
import torch
from huggingface_hub import snapshot_download
from safetensors.torch import load_file
from transformers import AutoTokenizer
from diffusers import AutoencoderKL, FlowMatchEulerDiscreteScheduler, OmniGenPipeline, OmniGenTransformer2DModel
def main(args):
# checkpoint from h... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_tiny_autoencoder_to_diffusers.py | scripts/convert_tiny_autoencoder_to_diffusers.py | import argparse
import safetensors.torch
from diffusers import AutoencoderTiny
"""
Example - From the diffusers root directory:
Download the weights:
```sh
$ wget -q https://huggingface.co/madebyollin/taesd/resolve/main/taesd_encoder.safetensors
$ wget -q https://huggingface.co/madebyollin/taesd/resolve/main/taesd... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_hunyuan_video_to_diffusers.py | scripts/convert_hunyuan_video_to_diffusers.py | import argparse
from typing import Any, Dict
import torch
from accelerate import init_empty_weights
from transformers import (
AutoModel,
AutoTokenizer,
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
LlavaForConditionalGeneration,
)
from diffusers import (
AutoencoderKLHunyuanVideo,
... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_kakao_brain_unclip_to_diffusers.py | scripts/convert_kakao_brain_unclip_to_diffusers.py | import argparse
import tempfile
import torch
from accelerate import load_checkpoint_and_dispatch
from transformers import CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import UnCLIPPipeline, UNet2DConditionModel, UNet2DModel
from diffusers.models.transformers.prior_transformer import PriorTransformer
from... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | true |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_models_diffuser_to_diffusers.py | scripts/convert_models_diffuser_to_diffusers.py | import json
import os
import torch
from diffusers import UNet1DModel
os.makedirs("hub/hopper-medium-v2/unet/hor32", exist_ok=True)
os.makedirs("hub/hopper-medium-v2/unet/hor128", exist_ok=True)
os.makedirs("hub/hopper-medium-v2/value_function", exist_ok=True)
def unet(hor):
if hor == 128:
down_block_... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_unidiffuser_to_diffusers.py | scripts/convert_unidiffuser_to_diffusers.py | # Convert the original UniDiffuser checkpoints into diffusers equivalents.
import argparse
from argparse import Namespace
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
GPT2Tokenizer... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/change_naming_configs_and_checkpoints.py | scripts/change_naming_configs_and_checkpoints.py | # 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... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/generate_logits.py | scripts/generate_logits.py | import random
import torch
from huggingface_hub import HfApi
from diffusers import UNet2DModel
api = HfApi()
results = {}
# fmt: off
results["google_ddpm_cifar10_32"] = torch.tensor([
-0.7515, -1.6883, 0.2420, 0.0300, 0.6347, 1.3433, -1.1743, -3.7467,
1.2342, -2.2485, 0.4636, 0.8076, -0.7991, 0.3969, 0.849... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_flux2_to_diffusers.py | scripts/convert_flux2_to_diffusers.py | import argparse
from contextlib import nullcontext
from typing import Any, Dict, Tuple
import safetensors.torch
import torch
from accelerate import init_empty_weights
from huggingface_hub import hf_hub_download
from transformers import AutoProcessor, GenerationConfig, Mistral3ForConditionalGeneration
from diffusers i... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_wan_to_diffusers.py | scripts/convert_wan_to_diffusers.py | import argparse
import pathlib
from typing import Any, Dict, Tuple
import torch
from accelerate import init_empty_weights
from huggingface_hub import hf_hub_download, snapshot_download
from safetensors.torch import load_file
from transformers import (
AutoProcessor,
AutoTokenizer,
CLIPImageProcessor,
C... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | true |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_ddpm_original_checkpoint_to_diffusers.py | scripts/convert_ddpm_original_checkpoint_to_diffusers.py | import argparse
import json
import torch
from diffusers import AutoencoderKL, DDPMPipeline, DDPMScheduler, UNet2DModel, VQModel
def shave_segments(path, n_shave_prefix_segments=1):
"""
Removes segments. Positive values shave the first segments, negative shave the last segments.
"""
if n_shave_prefix... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_ovis_image_to_diffusers.py | scripts/convert_ovis_image_to_diffusers.py | import argparse
from contextlib import nullcontext
import safetensors.torch
import torch
from accelerate import init_empty_weights
from huggingface_hub import hf_hub_download
from diffusers import OvisImageTransformer2DModel
from diffusers.utils.import_utils import is_accelerate_available
"""
# Transformer
python ... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_cogview4_to_diffusers_megatron.py | scripts/convert_cogview4_to_diffusers_megatron.py | """
Convert a CogView4 checkpoint from Megatron to the Diffusers format.
Example usage:
python scripts/convert_cogview4_to_diffusers.py \
--transformer_checkpoint_path 'your path/cogview4_6b/mp_rank_00/model_optim_rng.pt' \
--vae_checkpoint_path 'your path/cogview4_6b/imagekl_ch16.pt' \
--o... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_animatediff_motion_module_to_diffusers.py | scripts/convert_animatediff_motion_module_to_diffusers.py | import argparse
import torch
from safetensors.torch import load_file
from diffusers import MotionAdapter
def convert_motion_module(original_state_dict):
converted_state_dict = {}
for k, v in original_state_dict.items():
if "pos_encoder" in k:
continue
else:
converted... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_stable_audio.py | scripts/convert_stable_audio.py | # Run this script to convert the Stable Audio model weights to a diffusers pipeline.
import argparse
import json
import os
from contextlib import nullcontext
import torch
from safetensors.torch import load_file
from transformers import (
AutoTokenizer,
T5EncoderModel,
)
from diffusers import (
Autoencoder... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_hunyuan_video1_5_to_diffusers.py | scripts/convert_hunyuan_video1_5_to_diffusers.py | import argparse
import json
import os
import pathlib
import torch
from accelerate import init_empty_weights
from huggingface_hub import hf_hub_download, snapshot_download
from safetensors.torch import load_file
from transformers import (
AutoModel,
AutoTokenizer,
SiglipImageProcessor,
SiglipVisionModel... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | true |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_kandinsky3_unet.py | scripts/convert_kandinsky3_unet.py | #!/usr/bin/env python3
import argparse
import fnmatch
from safetensors.torch import load_file
from diffusers import Kandinsky3UNet
MAPPING = {
"to_time_embed.1": "time_embedding.linear_1",
"to_time_embed.3": "time_embedding.linear_2",
"in_layer": "conv_in",
"out_layer.0": "conv_norm_out",
"out_l... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_gligen_to_diffusers.py | scripts/convert_gligen_to_diffusers.py | import argparse
import re
import torch
import yaml
from transformers import (
CLIPProcessor,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionModelWithProjection,
)
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionGLIGENPipeline,
StableDiffusionGLIGENTextImagePipeline,
U... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_sana_to_diffusers.py | scripts/convert_sana_to_diffusers.py | #!/usr/bin/env python
from __future__ import annotations
import argparse
import os
from contextlib import nullcontext
import torch
from accelerate import init_empty_weights
from huggingface_hub import hf_hub_download, snapshot_download
from termcolor import colored
from transformers import AutoModelForCausalLM, AutoT... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_ncsnpp_original_checkpoint_to_diffusers.py | scripts/convert_ncsnpp_original_checkpoint_to_diffusers.py | # 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... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/extract_lora_from_model.py | scripts/extract_lora_from_model.py | """
This script demonstrates how to extract a LoRA checkpoint from a fully finetuned model with the CogVideoX model.
To make it work for other models:
* Change the model class. Here we use `CogVideoXTransformer3DModel`. For Flux, it would be `FluxTransformer2DModel`,
for example. (TODO: more reason to add `AutoModel`... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_vq_diffusion_to_diffusers.py | scripts/convert_vq_diffusion_to_diffusers.py | """
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... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | true |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_consistency_to_diffusers.py | scripts/convert_consistency_to_diffusers.py | import argparse
import os
import torch
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNet2DModel,
)
TEST_UNET_CONFIG = {
"sample_size": 32,
"in_channels": 3,
"out_channels": 3,
"layers_per_block": 2,
"num_class_embeds": 1000,
"block_out_channel... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_prx_to_diffusers.py | scripts/convert_prx_to_diffusers.py | #!/usr/bin/env python3
"""
Script to convert PRX checkpoint from original codebase to diffusers format.
"""
import argparse
import json
import os
import sys
from dataclasses import asdict, dataclass
from typing import Dict, Tuple
import torch
from safetensors.torch import save_file
from diffusers.models.transformers... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_hunyuandit_to_diffusers.py | scripts/convert_hunyuandit_to_diffusers.py | import argparse
import torch
from diffusers import HunyuanDiT2DModel
def main(args):
state_dict = torch.load(args.pt_checkpoint_path, map_location="cpu")
if args.load_key != "none":
try:
state_dict = state_dict[args.load_key]
except KeyError:
raise KeyError(
... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_lumina_to_diffusers.py | scripts/convert_lumina_to_diffusers.py | import argparse
import os
import torch
from safetensors.torch import load_file
from transformers import AutoModel, AutoTokenizer
from diffusers import AutoencoderKL, FlowMatchEulerDiscreteScheduler, LuminaNextDiT2DModel, LuminaPipeline
def main(args):
# checkpoint from https://huggingface.co/Alpha-VLLM/Lumina-N... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_cogview4_to_diffusers.py | scripts/convert_cogview4_to_diffusers.py | """
Convert a CogView4 checkpoint from SAT(https://github.com/THUDM/SwissArmyTransformer) to the Diffusers format.
(deprecated Since 2025-02-07 and will remove it in later CogView4 version)
This script converts a CogView4 checkpoint to the Diffusers format, which can then be used
with the Diffusers library.
Example u... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_music_spectrogram_to_diffusers.py | scripts/convert_music_spectrogram_to_diffusers.py | #!/usr/bin/env python3
import argparse
import os
import jax as jnp
import numpy as onp
import torch
import torch.nn as nn
from music_spectrogram_diffusion import inference
from t5x import checkpoints
from diffusers import DDPMScheduler, OnnxRuntimeModel, SpectrogramDiffusionPipeline
from diffusers.pipelines.spectrogr... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_original_audioldm2_to_diffusers.py | scripts/convert_original_audioldm2_to_diffusers.py | # 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... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | true |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_sd3_to_diffusers.py | scripts/convert_sd3_to_diffusers.py | import argparse
from contextlib import nullcontext
import safetensors.torch
import torch
from accelerate import init_empty_weights
from diffusers import AutoencoderKL, SD3Transformer2DModel
from diffusers.loaders.single_file_utils import convert_ldm_vae_checkpoint
from diffusers.models.model_loading_utils import load... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_stable_cascade_lite.py | scripts/convert_stable_cascade_lite.py | # Run this script to convert the Stable Cascade model weights to a diffusers pipeline.
import argparse
from contextlib import nullcontext
import torch
from safetensors.torch import load_file
from transformers import (
AutoTokenizer,
CLIPConfig,
CLIPImageProcessor,
CLIPTextModelWithProjection,
CLIPV... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_i2vgen_to_diffusers.py | scripts/convert_i2vgen_to_diffusers.py | # 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... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_if.py | scripts/convert_if.py | import argparse
import inspect
import os
import numpy as np
import torch
import yaml
from torch.nn import functional as F
from transformers import CLIPConfig, CLIPImageProcessor, CLIPVisionModelWithProjection, T5EncoderModel, T5Tokenizer
from diffusers import DDPMScheduler, IFPipeline, IFSuperResolutionPipeline, UNet... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | true |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_amused.py | scripts/convert_amused.py | import inspect
import os
from argparse import ArgumentParser
import numpy as np
import torch
from muse import MaskGiTUViT, VQGANModel
from muse import PipelineMuse as OldPipelineMuse
from transformers import CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import VQModel
from diffusers.models.attention_proce... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_pixart_alpha_to_diffusers.py | scripts/convert_pixart_alpha_to_diffusers.py | import argparse
import os
import torch
from transformers import T5EncoderModel, T5Tokenizer
from diffusers import AutoencoderKL, DPMSolverMultistepScheduler, PixArtAlphaPipeline, Transformer2DModel
ckpt_id = "PixArt-alpha/PixArt-alpha"
# https://github.com/PixArt-alpha/PixArt-alpha/blob/0f55e922376d8b797edd44d25d0e... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_sd3_controlnet_to_diffusers.py | scripts/convert_sd3_controlnet_to_diffusers.py | """
A script to convert Stable Diffusion 3.5 ControlNet checkpoints to the Diffusers format.
Example:
Convert a SD3.5 ControlNet checkpoint to Diffusers format using local file:
```bash
python scripts/convert_sd3_controlnet_to_diffusers.py \
--checkpoint_path "path/to/local/sd3.5_large_controlnet_c... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_vae_pt_to_diffusers.py | scripts/convert_vae_pt_to_diffusers.py | import argparse
import io
import requests
import torch
import yaml
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
renew_vae_attention_paths,
renew_vae_resnet_paths,
)
f... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_consistency_decoder.py | scripts/convert_consistency_decoder.py | import math
import os
import urllib
import warnings
from argparse import ArgumentParser
import torch
import torch.nn as nn
import torch.nn.functional as F
from huggingface_hub.utils import insecure_hashlib
from safetensors.torch import load_file as stl
from tqdm import tqdm
from diffusers import AutoencoderKL, Consis... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | true |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_svd_to_diffusers.py | scripts/convert_svd_to_diffusers.py | from diffusers.utils import is_accelerate_available, logging
if is_accelerate_available():
pass
logger = logging.get_logger(__name__) # pylint: disable=invalid-name
def create_unet_diffusers_config(original_config, image_size: int, controlnet=False):
"""
Creates a config for the diffusers based on the... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | true |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_vae_diff_to_onnx.py | scripts/convert_vae_diff_to_onnx.py | # Copyright 2022 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... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_aura_flow_to_diffusers.py | scripts/convert_aura_flow_to_diffusers.py | import argparse
import torch
from huggingface_hub import hf_hub_download
from diffusers.models.transformers.auraflow_transformer_2d import AuraFlowTransformer2DModel
def load_original_state_dict(args):
model_pt = hf_hub_download(repo_id=args.original_state_dict_repo_id, filename="aura_diffusion_pytorch_model.bi... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_zero123_to_diffusers.py | scripts/convert_zero123_to_diffusers.py | """
This script modified from
https://github.com/huggingface/diffusers/blob/bc691231360a4cbc7d19a58742ebb8ed0f05e027/scripts/convert_original_stable_diffusion_to_diffusers.py
Convert original Zero1to3 checkpoint to diffusers checkpoint.
# run the convert script
$ python convert_zero123_to_diffusers.py \
--checkpoi... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | true |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_blipdiffusion_to_diffusers.py | scripts/convert_blipdiffusion_to_diffusers.py | """
This script requires you to build `LAVIS` from source, since the pip version doesn't have BLIP Diffusion. Follow instructions here: https://github.com/salesforce/LAVIS/tree/main.
"""
import argparse
import os
import tempfile
import torch
from lavis.models import load_model_and_preprocess
from transformers import ... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_cogvideox_to_diffusers.py | scripts/convert_cogvideox_to_diffusers.py | import argparse
from typing import Any, Dict
import torch
from transformers import T5EncoderModel, T5Tokenizer
from diffusers import (
AutoencoderKLCogVideoX,
CogVideoXDDIMScheduler,
CogVideoXImageToVideoPipeline,
CogVideoXPipeline,
CogVideoXTransformer3DModel,
)
def reassign_query_key_value_inp... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_hunyuandit_controlnet_to_diffusers.py | scripts/convert_hunyuandit_controlnet_to_diffusers.py | import argparse
import torch
from diffusers import HunyuanDiT2DControlNetModel
def main(args):
state_dict = torch.load(args.pt_checkpoint_path, map_location="cpu")
if args.load_key != "none":
try:
state_dict = state_dict[args.load_key]
except KeyError:
raise KeyError... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_mochi_to_diffusers.py | scripts/convert_mochi_to_diffusers.py | import argparse
from contextlib import nullcontext
import torch
from accelerate import init_empty_weights
from safetensors.torch import load_file
from transformers import T5EncoderModel, T5Tokenizer
from diffusers import AutoencoderKLMochi, FlowMatchEulerDiscreteScheduler, MochiPipeline, MochiTransformer3DModel
from ... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_diffusers_sdxl_lora_to_webui.py | scripts/convert_diffusers_sdxl_lora_to_webui.py | # Script for converting a Hugging Face Diffusers trained SDXL LoRAs to Kohya format
# This means that you can input your diffusers-trained LoRAs and
# Get the output to work with WebUIs such as AUTOMATIC1111, ComfyUI, SD.Next and others.
# To get started you can find some cool `diffusers` trained LoRAs such as this cu... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_original_musicldm_to_diffusers.py | scripts/convert_original_musicldm_to_diffusers.py | # 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... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | true |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_animatediff_sparsectrl_to_diffusers.py | scripts/convert_animatediff_sparsectrl_to_diffusers.py | 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... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_stable_diffusion_checkpoint_to_onnx.py | scripts/convert_stable_diffusion_checkpoint_to_onnx.py | # 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... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/conversion_ldm_uncond.py | scripts/conversion_ldm_uncond.py | import argparse
import torch
import yaml
from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
def convert_ldm_original(checkpoint_path, config_path, output_path):
config = yaml.safe_load(config_path)
state_dict = torch.load(checkpoint_path, map_location="cpu")["model"]
keys = list(sta... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_asymmetric_vqgan_to_diffusers.py | scripts/convert_asymmetric_vqgan_to_diffusers.py | import argparse
import time
from pathlib import Path
from typing import Any, Dict, Literal
import torch
from diffusers import AsymmetricAutoencoderKL
ASYMMETRIC_AUTOENCODER_KL_x_1_5_CONFIG = {
"in_channels": 3,
"out_channels": 3,
"down_block_types": [
"DownEncoderBlock2D",
"DownEncoderBl... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_dcae_to_diffusers.py | scripts/convert_dcae_to_diffusers.py | import argparse
from typing import Any, Dict
import torch
from huggingface_hub import hf_hub_download
from safetensors.torch import load_file
from diffusers import AutoencoderDC
def remap_qkv_(key: str, state_dict: Dict[str, Any]):
qkv = state_dict.pop(key)
q, k, v = torch.chunk(qkv, 3, dim=0)
parent_mo... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_stable_diffusion_controlnet_to_tensorrt.py | scripts/convert_stable_diffusion_controlnet_to_tensorrt.py | import argparse
import sys
import tensorrt as trt
def convert_models(onnx_path: str, num_controlnet: int, output_path: str, fp16: bool = False, sd_xl: bool = False):
"""
Function to convert models in stable diffusion controlnet pipeline into TensorRT format
Example:
python convert_stable_diffusion_c... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_versatile_diffusion_to_diffusers.py | scripts/convert_versatile_diffusion_to_diffusers.py | # 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... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | true |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_skyreelsv2_to_diffusers.py | scripts/convert_skyreelsv2_to_diffusers.py | import argparse
import os
import pathlib
from typing import Any, Dict
import torch
from accelerate import init_empty_weights
from huggingface_hub import hf_hub_download
from safetensors.torch import load_file
from transformers import AutoProcessor, AutoTokenizer, CLIPVisionModelWithProjection, UMT5EncoderModel
from d... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_pixart_sigma_to_diffusers.py | scripts/convert_pixart_sigma_to_diffusers.py | import argparse
import os
import torch
from transformers import T5EncoderModel, T5Tokenizer
from diffusers import AutoencoderKL, DPMSolverMultistepScheduler, PixArtSigmaPipeline, Transformer2DModel
ckpt_id = "PixArt-alpha"
# https://github.com/PixArt-alpha/PixArt-sigma/blob/dd087141864e30ec44f12cb7448dd654be065e88/... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/__init__.py | scripts/__init__.py | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false | |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_animatediff_motion_lora_to_diffusers.py | scripts/convert_animatediff_motion_lora_to_diffusers.py | import argparse
import os
import torch
from huggingface_hub import create_repo, upload_folder
from safetensors.torch import load_file, save_file
def convert_motion_module(original_state_dict):
converted_state_dict = {}
for k, v in original_state_dict.items():
if "pos_encoder" in k:
contin... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_stable_diffusion_controlnet_to_onnx.py | scripts/convert_stable_diffusion_controlnet_to_onnx.py | import argparse
import os
import shutil
from pathlib import Path
import onnx
import onnx_graphsurgeon as gs
import torch
from onnx import shape_inference
from packaging import version
from polygraphy.backend.onnx.loader import fold_constants
from torch.onnx import export
from diffusers import (
ControlNetModel,
... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_k_upscaler_to_diffusers.py | scripts/convert_k_upscaler_to_diffusers.py | import argparse
import huggingface_hub
import k_diffusion as K
import torch
from diffusers import UNet2DConditionModel
UPSCALER_REPO = "pcuenq/k-upscaler"
def resnet_to_diffusers_checkpoint(resnet, checkpoint, *, diffusers_resnet_prefix, resnet_prefix):
rv = {
# norm1
f"{diffusers_resnet_prefi... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_original_audioldm_to_diffusers.py | scripts/convert_original_audioldm_to_diffusers.py | # 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... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | true |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_original_stable_diffusion_to_diffusers.py | scripts/convert_original_stable_diffusion_to_diffusers.py | # 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... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_kandinsky_to_diffusers.py | scripts/convert_kandinsky_to_diffusers.py | import argparse
import os
import tempfile
import torch
from accelerate import load_checkpoint_and_dispatch
from diffusers import UNet2DConditionModel
from diffusers.models.transformers.prior_transformer import PriorTransformer
from diffusers.models.vq_model import VQModel
"""
Example - From the diffusers root direc... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | true |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_unclip_txt2img_to_image_variation.py | scripts/convert_unclip_txt2img_to_image_variation.py | 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... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_ltx_to_diffusers.py | scripts/convert_ltx_to_diffusers.py | import argparse
from pathlib import Path
from typing import Any, Dict
import torch
from accelerate import init_empty_weights
from safetensors.torch import load_file
from transformers import T5EncoderModel, T5Tokenizer
from diffusers import (
AutoencoderKLLTXVideo,
FlowMatchEulerDiscreteScheduler,
LTXCondi... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_wuerstchen.py | scripts/convert_wuerstchen.py | # Run inside root directory of official source code: https://github.com/dome272/wuerstchen/
import os
import torch
from transformers import AutoTokenizer, CLIPTextModel
from vqgan import VQModel
from diffusers import (
DDPMWuerstchenScheduler,
WuerstchenCombinedPipeline,
WuerstchenDecoderPipeline,
Wue... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_dance_diffusion_to_diffusers.py | scripts/convert_dance_diffusion_to_diffusers.py | #!/usr/bin/env python3
import argparse
import math
import os
from copy import deepcopy
import requests
import torch
from audio_diffusion.models import DiffusionAttnUnet1D
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNet1DModel
from diffusers.utils.... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_dit_to_diffusers.py | scripts/convert_dit_to_diffusers.py | import argparse
import os
import torch
from torchvision.datasets.utils import download_url
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, Transformer2DModel
pretrained_models = {512: "DiT-XL-2-512x512.pt", 256: "DiT-XL-2-256x256.pt"}
def download_model(model_name):
"""
Downloads a pre-tr... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_sana_controlnet_to_diffusers.py | scripts/convert_sana_controlnet_to_diffusers.py | #!/usr/bin/env python
from __future__ import annotations
import argparse
from contextlib import nullcontext
import torch
from accelerate import init_empty_weights
from diffusers import (
SanaControlNetModel,
)
from diffusers.models.model_loading_utils import load_model_dict_into_meta
from diffusers.utils.import_... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_cogview3_to_diffusers.py | scripts/convert_cogview3_to_diffusers.py | """
Convert a CogView3 checkpoint to the Diffusers format.
This script converts a CogView3 checkpoint to the Diffusers format, which can then be used
with the Diffusers library.
Example usage:
python scripts/convert_cogview3_to_diffusers.py \
--transformer_checkpoint_path 'your path/cogview3plus_3b/1/mp_r... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_shap_e_to_diffusers.py | scripts/convert_shap_e_to_diffusers.py | import argparse
import tempfile
import torch
from accelerate import load_checkpoint_and_dispatch
from diffusers.models.transformers.prior_transformer import PriorTransformer
from diffusers.pipelines.shap_e import ShapERenderer
"""
Example - From the diffusers root directory:
Download weights:
```sh
$ wget "https:... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | true |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_flux_to_diffusers.py | scripts/convert_flux_to_diffusers.py | import argparse
from contextlib import nullcontext
import safetensors.torch
import torch
from accelerate import init_empty_weights
from huggingface_hub import hf_hub_download
from diffusers import AutoencoderKL, FluxTransformer2DModel
from diffusers.loaders.single_file_utils import convert_ldm_vae_checkpoint
from dif... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_stable_cascade.py | scripts/convert_stable_cascade.py | # Run this script to convert the Stable Cascade model weights to a diffusers pipeline.
import argparse
from contextlib import nullcontext
import torch
from safetensors.torch import load_file
from transformers import (
AutoTokenizer,
CLIPConfig,
CLIPImageProcessor,
CLIPTextModelWithProjection,
CLIPV... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_original_t2i_adapter.py | scripts/convert_original_t2i_adapter.py | # 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... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_flux_xlabs_ipadapter_to_diffusers.py | scripts/convert_flux_xlabs_ipadapter_to_diffusers.py | import argparse
from contextlib import nullcontext
import safetensors.torch
from accelerate import init_empty_weights
from huggingface_hub import hf_hub_download
from diffusers.utils.import_utils import is_accelerate_available, is_transformers_available
if is_transformers_available():
from transformers import C... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_diffusers_to_original_sdxl.py | scripts/convert_diffusers_to_original_sdxl.py | # Script for converting a HF Diffusers saved pipeline to a Stable Diffusion checkpoint.
# *Only* converts the UNet, VAE, and Text Encoder.
# Does not convert optimizer state or any other thing.
import argparse
import os.path as osp
import re
import torch
from safetensors.torch import load_file, save_file
# ========... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_sana_video_to_diffusers.py | scripts/convert_sana_video_to_diffusers.py | #!/usr/bin/env python
from __future__ import annotations
import argparse
import os
from contextlib import nullcontext
import torch
from accelerate import init_empty_weights
from huggingface_hub import hf_hub_download, snapshot_download
from termcolor import colored
from transformers import AutoModelForCausalLM, AutoT... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_original_controlnet_to_diffusers.py | scripts/convert_original_controlnet_to_diffusers.py | # 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... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_cosmos_to_diffusers.py | scripts/convert_cosmos_to_diffusers.py | """
# Cosmos 2 Predict
Download checkpoint
```bash
hf download nvidia/Cosmos-Predict2-2B-Text2Image
```
convert checkpoint
```bash
transformer_ckpt_path=~/.cache/huggingface/hub/models--nvidia--Cosmos-Predict2-2B-Text2Image/snapshots/acdb5fde992a73ef0355f287977d002cbfd127e0/model.pt
python scripts/convert_cosmos_to_... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
huggingface/diffusers | https://github.com/huggingface/diffusers/blob/47378066c002573613a1dba686570fbd5a1cf48a/scripts/convert_ldm_original_checkpoint_to_diffusers.py | scripts/convert_ldm_original_checkpoint_to_diffusers.py | # 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... | python | Apache-2.0 | 47378066c002573613a1dba686570fbd5a1cf48a | 2026-01-04T14:42:56.953111Z | false |
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