Delete app.py

app.py

@@ -1,45 +0,0 @@
-import gradio as gr
-import torch
-from shap_e.diffusion.sample import sample_latents
-from shap_e.diffusion.gaussian_diffusion import diffusion_from_config
-from shap_e.models.download import load_model, load_config
-from shap_e.util.notebooks import decode_latent_mesh
-import zipfile
-import io
-
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-
-# Load models
-transmitter = load_model("transmitter", device=device)
-xm = load_model("text300M", device=device)
-diffusion = diffusion_from_config(load_config("diffusion"))
-
-def generate_3d(prompt):
-    with torch.no_grad():
-        latents = sample_latents(
-            batch_size=1,
-            model=xm,
-            diffusion=diffusion,
-            guidance_scale=3.0,
-            model_kwargs=dict(texts=[prompt]),
-            progress=True,
-            clip_denoised=True,
-            use_fp16=True,
-            device=device,
-        )
-        mesh = decode_latent_mesh(xm, latents[0]).tri_mesh()
-
-        # Save zip
-        buf = io.BytesIO()
-        with zipfile.ZipFile(buf, "w") as z:
-            z.writestr("mesh.ply", mesh.to_ply())
-        buf.seek(0)
-        return buf
-
-demo = gr.Interface(
-    fn=generate_3d,
-    inputs=gr.Textbox(label="Prompt"),
-    outputs=gr.File(label="Generated 3D Model (.zip)")
-)
-
-demo.launch()