chore: update description

app.py

@@ -12,16 +12,35 @@ import gradio as gr
 
 from modeling_siglip import SiglipForImageClassification
 
-MODEL_NAME = "p1atdev/siglip-tagger-test-3"
+MODEL_NAME = os.environ["MODEL_NAME"]
 PROCESSOR_NAME = MODEL_NAME
 HF_TOKEN = os.environ["HF_READ_TOKEN"]
 
 EXAMPLES = [["./images/sample.jpg"], ["./images/sample2.webp"]]
 
+README_MD = """\
+## SigLIP Tagger Test 3
+An experimental model for tagging danbooru tags of images using SigLIP.
+
+Model(s):
+- [p1atdev/siglip-tagger-test-3](https://huggingface.co/p1atdev/siglip-tagger-test-3)
+
+Example images by NovelAI and niji・journey.
+"""
+
 model = SiglipForImageClassification.from_pretrained(MODEL_NAME, token=HF_TOKEN)
-# model = torch.compile(model)
 processor = AutoImageProcessor.from_pretrained(PROCESSOR_NAME, token=HF_TOKEN)
 
+try:
+    print("torch.compile")
+    model = torch.compile(model)
+    # warmup
+    print("warming up...")
+    model(**processor(Image.open(EXAMPLES[0][0]), return_tensors="pt"))
+    print("done")
+except:
+    print("torch.compile not supported")
+
 
 def compose_text(results: dict[str, float], threshold: float = 0.3):
     return ", ".join(
@@ -65,18 +84,7 @@ css = """\
 
 def demo():
     with gr.Blocks(css=css) as ui:
-        gr.Markdown(
-            """\
-## SigLIP Tagger Test 3
-An experimental model for tagging danbooru tags of images using SigLIP.
-
-Models:
-- (soon)
-
-Example images by NovelAI and niji・journey.
-
-"""
-        )
+        gr.Markdown(README_MD)
 
         with gr.Row():
             with gr.Column():