from transformers import GPT2Config, AutoConfig
from diffusers import StableDiffusionPipeline

model_name = "somq/fantassified_icons_v2"
# model_name = "updated_model"


# model = AutoModelForSequenceClassification.from_pretrained(model_name)
# print(model)

# config = AutoConfig.from_pretrained(model_name)
# print(config)

model = StableDiffusionPipeline.from_pretrained(model_name)
# image = model("a photograph of an astronaut riding a horse").images[0]
# print(image)


# Load the existing configuration and model
# existing_config = GPT2Config.from_pretrained("your_model_name_or_path")
# existing_model = GPT2ForTextToImage.from_pretrained("your_model_name_or_path")

# Update the configuration as needed
# updated_config = existing_config  # Modify as needed

# Save the updated model and configuration
# updated_model_path = "./updated_model"
updated_model_path = "./"
# updated_config.save_pretrained(updated_model_path)
model.save_pretrained(updated_model_path)