chatbot try

app.py

@@ -1,7 +1,26 @@
+from unsloth import FastLanguageModel
+from peft import PeftModel
+from transformers import AutoTokenizer
 import gradio as gr
 
-def greet(name):
-    return "Hello " + name + "!!"
+base_model_name = "unsloth/Llama-3.2-3B-Instruct"
+base_model, tokenizer = FastLanguageModel.from_pretrained(
+    model_name=base_model_name,
+    max_seq_length=2048,
+    dtype=None,
+    load_in_4bit=True 
+)
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+# lora adapters from my Hugging Face model
+lora_model_name = "oskaralf/lora_model"  # Hugging Face repository for LoRA adapters
+model = PeftModel.from_pretrained(base_model, lora_model_name)
+FastLanguageModel.for_inference(model)
+
+def chatbot(input_text):
+    inputs = tokenizer(input_text, return_tensors="pt").to("cuda")  
+    outputs = model.generate(input_ids=inputs["input_ids"], max_new_tokens=64)
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return response
+
+iface = gr.Interface(fn=chatbot, inputs="text", outputs="text", title="Chatbot")
+iface.launch()