mirror of
https://github.com/vladmandic/automatic
synced 2026-09-13 01:59:42 +02:00
CalamitousFelicitousness
e7d2e28d3d
ChronoEdit, HunyuanImage, Kandinsky5, LongCat, Ovis, NucleusMoE, Bria, BriaFibo. Each inherits from_single_file via FromOriginalModelMixin but has no SINGLE_FILE_LOADABLE_CLASSES entry; calling it crashed with "FromOriginalModelMixin is currently only compatible with [...]". TransformerSpec(cls=...) for each. Bria specs in pipelines/bria/__init__.py; the rest are module-level in model_<arch>.py since they have no package directory.
49 lines
2.0 KiB
Python
49 lines
2.0 KiB
Python
import transformers
|
|
import diffusers
|
|
from modules import shared, devices, sd_models, model_quant, sd_hijack_te
|
|
from modules.logger import log
|
|
from pipelines import generic
|
|
from pipelines.native_transformer import TransformerSpec
|
|
|
|
|
|
LONGCAT_SPEC = TransformerSpec(cls=diffusers.LongCatImageTransformer2DModel)
|
|
|
|
|
|
def load_longcat(checkpoint_info, diffusers_load_config=None):
|
|
if diffusers_load_config is None:
|
|
diffusers_load_config = {}
|
|
repo_id = sd_models.path_to_repo(checkpoint_info)
|
|
sd_models.hf_auth_check(checkpoint_info)
|
|
|
|
load_args, _quant_args = model_quant.get_dit_args(diffusers_load_config, allow_quant=False)
|
|
log.debug(f'Load model: type=LongCat repo="{repo_id}" config={diffusers_load_config} offload={shared.opts.diffusers_offload_mode} dtype={devices.dtype} args={diffusers_load_config}')
|
|
|
|
transformer = generic.load_transformer(repo_id, cls_name=diffusers.LongCatImageTransformer2DModel, load_config=diffusers_load_config, native_spec=LONGCAT_SPEC)
|
|
text_encoder = generic.load_text_encoder(repo_id, cls_name=transformers.Qwen2_5_VLForConditionalGeneration, load_config=diffusers_load_config)
|
|
text_processor = transformers.Qwen2VLProcessor.from_pretrained(repo_id, subfolder='tokenizer', cache_dir=shared.opts.hfcache_dir)
|
|
|
|
if 'edit' in repo_id.lower():
|
|
cls = diffusers.LongCatImageEditPipeline
|
|
else:
|
|
cls = diffusers.LongCatImagePipeline
|
|
|
|
pipe = cls.from_pretrained(
|
|
repo_id,
|
|
cache_dir=shared.opts.diffusers_dir,
|
|
transformer=transformer,
|
|
text_encoder=text_encoder,
|
|
text_processor=text_processor,
|
|
**load_args,
|
|
)
|
|
diffusers.pipelines.auto_pipeline.AUTO_TEXT2IMAGE_PIPELINES_MAPPING["longcat"] = cls
|
|
diffusers.pipelines.auto_pipeline.AUTO_IMAGE2IMAGE_PIPELINES_MAPPING["longcat"] = cls
|
|
diffusers.pipelines.auto_pipeline.AUTO_INPAINT_PIPELINES_MAPPING["longcat"] = cls
|
|
|
|
del transformer
|
|
del text_encoder
|
|
del text_processor
|
|
sd_hijack_te.init_hijack(pipe)
|
|
|
|
devices.torch_gc(force=True, reason='load')
|
|
return pipe
|