Add application file

app.py

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+import gradio as gr
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+# Load model + tokenizer
+model_id = "MahiH/dialogpt-finetuned-chatbot"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id)
+model.eval()
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model.to(device)
+
+# Inference function
+def chat(prompt):
+    input_text = f"Human: {prompt}\nAssistant: "
+    input_ids = tokenizer.encode(input_text, return_tensors="pt").to(device)
+
+    with torch.no_grad():
+        output_ids = model.generate(
+            input_ids,
+            max_new_tokens=100,
+            do_sample=True,
+            top_k=50,
+            top_p=0.95,
+            temperature=0.8,
+            pad_token_id=tokenizer.eos_token_id
+        )
+    
+    response = tokenizer.decode(output_ids[0], skip_special_tokens=True)
+    return response.split("Assistant:")[-1].strip()
+
+# Set up Gradio app (no UI, just API)
+app = gr.Interface(fn=chat, inputs=gr.Text(), outputs=gr.Text())
+
+app.launch()

requirements.txt

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+# requirements.txt
+transformers
+torch
+gradio