Create app.py

app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
+import torch
+
+# Load Zephyr model
+model_id = "HuggingFaceH4/zephyr-7b-beta"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.float16, device_map="auto")
+
+pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+# Chat function
+def chat_with_bot(user_input):
+    system_message = "You are a helpful, honest, and friendly assistant."
+    prompt = f"<|system|>\n{system_message}\n<|user|>\n{user_input}\n<|assistant|>\n"
+    response = pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_p=0.9)[0]["generated_text"]
+    answer = response.split("<|assistant|>")[-1].strip()
+    return answer
+
+# Gradio interface
+iface = gr.Interface(fn=chat_with_bot, 
+                     inputs=gr.Textbox(lines=2, placeholder="Ask me anything..."), 
+                     outputs="text",
+                     title="Zephyr Chatbot",
+                     description="Ask general questions and get helpful answers!")
+
+iface.launch()