Create app.py

app.py

@@ -0,0 +1,31 @@
+import torch
+from transformers import GPT2LMHeadModel, GPT2Tokenizer
+import gradio as gr
+
+# Load from your HF model repo
+model_name = "your-username/gpt2-phostune-demo"  # ✅ Replace
+
+tokenizer = GPT2Tokenizer.from_pretrained(model_name)
+model = GPT2LMHeadModel.from_pretrained(model_name)
+model.eval().to("cuda" if torch.cuda.is_available() else "cpu")
+
+def generate(prompt):
+    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+    outputs = model.generate(
+        **inputs,
+        max_new_tokens=100,
+        do_sample=True,
+        temperature=0.7,
+        top_k=50,
+        top_p=0.95
+    )
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+gr.Interface(
+    fn=generate,
+    inputs="text",
+    outputs="text",
+    title="🧠 PhosTune GPT-2 Demo",
+    description="Fine-tuned GPT-2 model deployed using Hugging Face Spaces.",
+    theme="compact"
+).launch()