Add chatbpot file

app.py

@@ -0,0 +1,38 @@
+import torch
+from transformers import AutoTokenizer
+from auto_gptq import AutoGPTQForCausalLM
+import gradio as gr
+
+checkpoint = "cortecs/Meta-Llama-3-8B-Instruct-GPTQ-8b"
+
+# Load tokenizer
+tokenizer = AutoTokenizer.from_pretrained(checkpoint, use_fast=True)
+
+# Load GPTQ model 
+
+model = AutoGPTQForCausalLM.from_quantized(
+    checkpoint,
+    device="cuda:0" if torch.cuda.is_available() else "cpu",
+    torch_dtype=torch.float16,
+)
+
+# Function to format prompt + generate response
+def predict(message, history):
+    prompt = f"<s>[INST] {message.strip()} [/INST]"
+    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+
+    outputs = model.generate(
+        **inputs,
+        do_sample=True,
+        temperature=0.6,
+        top_p=0.9,
+        max_new_tokens=256,
+        eos_token_id=tokenizer.eos_token_id
+    )
+
+    decoded = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    response = decoded.split("[/INST]")[-1].strip()
+    return response
+
+# Launch Gradio chatbot
+gr.ChatInterface(predict, title=" LLaMA 3 Chatbot").launch(debug=True)