mirror of https://github.com/vladmandic/automatic
47 lines
1.8 KiB
Python
47 lines
1.8 KiB
Python
import diffusers
|
|
from modules import shared, devices, sd_models, model_quant, sd_hijack_te
|
|
|
|
|
|
def load_omnigen2(checkpoint_info, diffusers_load_config={}): # pylint: disable=unused-argument
|
|
repo_id = sd_models.path_to_repo(checkpoint_info)
|
|
|
|
from pipelines.omnigen2 import OmniGen2Pipeline, OmniGen2Transformer2DModel, Qwen2_5_VLForConditionalGeneration
|
|
diffusers.OmniGen2Pipeline = OmniGen2Pipeline # monkey-pathch
|
|
diffusers.pipelines.auto_pipeline.AUTO_TEXT2IMAGE_PIPELINES_MAPPING["omnigen2"] = diffusers.OmniGen2Pipeline
|
|
diffusers.pipelines.auto_pipeline.AUTO_IMAGE2IMAGE_PIPELINES_MAPPING["omnigen2"] = diffusers.OmniGen2Pipeline
|
|
diffusers.pipelines.auto_pipeline.AUTO_INPAINT_PIPELINES_MAPPING["omnigen2"] = diffusers.OmniGen2Pipeline
|
|
|
|
load_config, quant_config = model_quant.get_dit_args(diffusers_load_config, module='Model')
|
|
transformer = OmniGen2Transformer2DModel.from_pretrained(
|
|
repo_id,
|
|
subfolder="transformer",
|
|
cache_dir=shared.opts.diffusers_dir,
|
|
trust_remote_code=True,
|
|
**load_config,
|
|
**quant_config,
|
|
)
|
|
|
|
load_config, quant_config = model_quant.get_dit_args(diffusers_load_config, module='TE')
|
|
mllm = Qwen2_5_VLForConditionalGeneration.from_pretrained(
|
|
repo_id,
|
|
subfolder="mllm",
|
|
cache_dir=shared.opts.diffusers_dir,
|
|
trust_remote_code=True,
|
|
**load_config,
|
|
**quant_config,
|
|
)
|
|
|
|
pipe = OmniGen2Pipeline.from_pretrained(
|
|
repo_id,
|
|
# transformer=transformer,
|
|
mllm=mllm,
|
|
cache_dir=shared.opts.diffusers_dir,
|
|
trust_remote_code=True,
|
|
**load_config,
|
|
)
|
|
pipe.transformer = transformer # for omnigen2 transformer must be loaded after pipeline
|
|
|
|
sd_hijack_te.init_hijack(pipe)
|
|
devices.torch_gc(force=True, reason='load')
|
|
return pipe
|