Create app.py

app.py

@@ -0,0 +1,49 @@
+import torch
+import gradio as gr
+from diffusers import DiffusionPipeline
+
+torch.set_num_threads(torch.get_num_threads())
+torch.set_float32_matmul_precision("high")
+
+pipe = DiffusionPipeline.from_pretrained(
+    "stablediffusionapi/anything-v5",
+    torch_dtype=torch.float32
+)
+pipe = pipe.to("cpu")
+
+def generate(prompt, steps, seed):
+    generator = torch.Generator(device="cpu").manual_seed(seed)
+
+    for i, out in enumerate(pipe(
+        prompt=prompt,
+        num_inference_steps=steps,
+        generator=generator,
+        callback_steps=1,
+        callback=lambda step, t, latents: None
+    )):
+        yield gr.Progress((i + 1) / steps), out.images[0]
+
+with gr.Blocks() as demo:
+    gr.Markdown("## 🌀 Anything-V5 CPU Anime Generator")
+
+    with gr.Row():
+        prompt = gr.Textbox(
+            label="Prompt",
+            value="Astronaut in a jungle, cold color palette, muted colors, detailed, anime style"
+        )
+
+    with gr.Row():
+        steps = gr.Slider(10, 40, value=25, step=1, label="Steps")
+        seed = gr.Number(value=42, precision=0, label="Seed")
+
+    output = gr.Image(type="pil", label="Result")
+
+    btn = gr.Button("Generate")
+
+    btn.click(
+        fn=generate,
+        inputs=[prompt, steps, seed],
+        outputs=output
+    )
+
+demo.launch()