from huggingface_hub import snapshot_download import gradio as gr # Download the model to cache or local dir local_dir = snapshot_download(repo_id="cloudqi/cqi_text_to_image_pt_v0") def show_path(): return f"Model downloaded to: {local_dir}" gr.Interface(fn=show_path, inputs=None, outputs="text").launch() demo.launch(share=True) from diffusers import DiffusionPipeline pipe = DiffusionPipeline.from_pretrained("cloudqi/cqi_text_to_image_pt_v0") prompt = "Gato em alta qualidade na neve\n" image = pipe(prompt).images[0]