Create app.py

app.py

@@ -0,0 +1,22 @@
+from transformers import AutoTokenizer, AutoModelForCausalLM
+from transformers import pipeline
+from streamlit import title, input_text, button, text
+
+# Define model and tokenizer
+model_name = "gokul00060/loora-chat-arm"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Create pipeline for inference
+chat_pipeline = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+# Streamlit app
+title("Chat with Lora Adaptor")
+
+text_input = input_text("Enter your message:")
+
+if button("Send"):
+  # Generate response
+  response = chat_pipeline(text_input, max_length=1024)
+  text(f"Lora: {response[0]['text']}")
+