Upload app.py

app.py

@@ -0,0 +1,38 @@
+# app.py
+import streamlit as st
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+def generate_kannada_text(prompt):
+    model_name = "Tensoic/Kan-LLaMA-7B-SFT-v0.1"
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    model = AutoModelForCausalLM.from_pretrained(model_name)
+
+    input_ids = tokenizer.encode(prompt, return_tensors="pt")
+
+    output = model.generate(
+        input_ids,
+        max_length=150,
+        num_beams=5,
+        no_repeat_ngram_size=2,
+        top_k=50,
+        top_p=0.95,
+        length_penalty=0.8
+    )
+
+    generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
+    return generated_text
+
+def main():
+    st.title("Kannada Text Generation App")
+
+    # User input prompt
+    prompt = st.text_area("Enter a prompt in Kannada:")
+
+    # Generate Kannada text
+    if st.button("Generate Text"):
+        generated_text = generate_kannada_text(prompt)
+        st.subheader("Generated Kannada Text:")
+        st.write(generated_text)
+
+if __name__ == "__main__":
+    main()