Create app.py

app.py

@@ -0,0 +1,29 @@
+import streamlit as st
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+# Streamlit App Title
+st.title("Tamil Text Generation with LLaMA")
+
+# Load the model and tokenizer
+model_name = "abhinand/tamil-llama-7b-base-v0.1"
+st.sidebar.write("Loading the model... This may take some time.")
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+st.sidebar.write("Model loaded successfully!")
+
+# Text input from the user
+input_text = st.text_area("Enter Tamil text:", "வணக்கம், எப்படி இருக்கின்றீர்கள்?")
+
+# Generate button
+if st.button("Generate Text"):
+    with st.spinner("Generating response..."):
+        # Encode the input text
+        inputs = tokenizer(input_text, return_tensors="pt")
+
+        # Generate response
+        outputs = model.generate(**inputs, max_length=50)
+
+        # Decode and display the generated text
+        generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+        st.text_area("Generated Response:", generated_text, height=200)