Added Gradio app

app.py

@@ -0,0 +1,36 @@
+import torch
+from peft import AutoPeftModelForCausalLM
+from transformers import AutoTokenizer, pipeline
+import gradio as gr
+
+
+peft_model_id = "Pr123/TinyLlama-EA-Chat"
+
+# Load Model with PEFT adapter
+model = AutoPeftModelForCausalLM.from_pretrained(
+    peft_model_id,
+    device_map="auto",
+    torch_dtype=torch.float16
+)
+tokenizer = AutoTokenizer.from_pretrained(peft_model_id)
+pipe = pipeline("text-generation", model=model, tokenizer=tokenizer, max_length=500)
+
+
+def chat_with_tinyllm(prompt):
+    instruction = "Answer the following question: if you don't know the answer, just say that you don't know; don't try to make up an answer."
+    prompt_content = f"<s>[INST] <<SYS>>{instruction}<</SYS>>{prompt}[/INST]"
+    result = pipe(prompt_content)
+    result = result[0]['generated_text'].split('[/INST]')[-1]
+    return result
+
+def chat_interface():
+    iface = gr.Interface(
+        fn=chat_with_tinyllm,
+        inputs=gr.inputs.Textbox(lines=2, placeholder="Type your question here..."),  
+        outputs="text",
+        title="Chat with TinyLlama",
+        description="This is a simple chatbot powered by a fine-tuned model on Hugging Face. If it doesn't know the answer, it will say so.")
+    return iface
+
+iface = chat_interface()
+iface.launch()

requirements.txt

@@ -0,0 +1,3 @@
+torch
+transformers
+gradio