GenAI-Arena / model /models /__init__.py
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from .imagenhub_models import load_imagenhub_model
from .playground_api import load_playground_model
from .fal_api_models import load_fal_model
from .videogenhub_models import load_videogenhub_model
# IMAGE_GENERATION_MODELS = ['fal_LCM(v1.5/XL)_text2image','fal_SDXLTurbo_text2image','fal_SDXL_text2image', 'imagenhub_PixArtAlpha_generation', 'fal_PixArtSigma_text2image',
# 'imagenhub_OpenJourney_generation','fal_SDXLLightning_text2image', 'fal_StableCascade_text2image',
# 'playground_PlayGroundV2_generation', 'playground_PlayGroundV2.5_generation']
IMAGE_GENERATION_MODELS = ['imagenhub_SDXLTurbo_generation','imagenhub_SDXL_generation', 'imagenhub_PixArtAlpha_generation',
'imagenhub_OpenJourney_generation','imagenhub_SDXLLightning_generation', 'imagenhub_StableCascade_generation',
'playground_PlayGroundV2_generation', 'playground_PlayGroundV2.5_generation']
IMAGE_EDITION_MODELS = ['imagenhub_CycleDiffusion_edition', 'imagenhub_Pix2PixZero_edition', 'imagenhub_Prompt2prompt_edition',
'imagenhub_SDEdit_edition', 'imagenhub_InstructPix2Pix_edition',
'imagenhub_MagicBrush_edition', 'imagenhub_PNP_edition',
'imagenhub_InfEdit_edition', 'imagenhub_CosXLEdit_edition']
VIDEO_GENERATION_MODELS = ['fal_AnimateDiff_text2video',
'fal_AnimateDiffTurbo_text2video',
#'fal_StableVideoDiffusion_text2video',
'videogenhub_LaVie_generation', 'videogenhub_VideoCrafter2_generation',
'videogenhub_ModelScope_generation', 'videogenhub_OpenSora_generation']
def load_pipeline(model_name):
"""
Load a model pipeline based on the model name
Args:
model_name (str): The name of the model to load, should be of the form {source}_{name}_{type}
the source can be either imagenhub or playground
the name is the name of the model used to load the model
the type is the type of the model, either generation or edition
"""
model_source, model_name, model_type = model_name.split("_")
if model_source == "imagenhub":
pipe = load_imagenhub_model(model_name, model_type)
elif model_source == "playground":
pipe = load_playground_model(model_name)
elif model_source == "fal":
pipe = load_fal_model(model_name, model_type)
elif model_source == "videogenhub":
pipe = load_videogenhub_model(model_name)
else:
raise ValueError(f"Model source {model_source} not supported")
return pipe