Create app.py

app.py

@@ -0,0 +1,41 @@
+import streamlit as st
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+# Define model path on Hugging Face Hub
+model_name = "Somya1834/fc-deepseek-finetuned-50"  # Replace with your repo
+
+# Load tokenizer and model from Hugging Face
+@st.cache_resource
+def load_model():
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    model = AutoModelForCausalLM.from_pretrained(model_name)
+    device = "cuda" if torch.cuda.is_available() else "cpu"
+    model.to(device)
+    return tokenizer, model, device
+
+# Load model once when app starts
+tokenizer, model, device = load_model()
+
+# Streamlit UI
+st.title("🚀 AI Chatbot - Powered by Your Fine-Tuned Model!")
+st.markdown("Ask me anything and get an AI-generated response!")
+
+# User input
+prompt = st.text_area("Enter your query:", "")
+
+# Generate response when button is clicked
+if st.button("Generate Response"):
+    if prompt.strip() != "":
+        # Tokenize input
+        inputs = tokenizer(prompt, return_tensors="pt", max_length=512, truncation=True, padding=True).to(device)
+
+        # Generate response
+        with torch.no_grad():
+            outputs = model.generate(**inputs, max_length=512, num_return_sequences=1)
+
+        # Decode and display the generated response
+        response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+        st.success(f"💬 Response: {response}")
+    else:
+        st.warning("Please enter a query to generate a response.")