Update app.py

app.py

@@ -0,0 +1,50 @@
+import spaces
+import torch
+from threading import Thread
+from transformers import AutoTokenizer, AutoModelForCausalLM, TextIteratorStreamer
+import gradio as gr
+MODEL_ID = "NoesisLab/Kai-30B-Instruct"
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_ID, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(
+    "NoesisLab/Spartacus-1B-Instruct",
+)
+
+@spaces.GPU
+def respond(message, history):
+    messages = [{"role": "system", "content": "You are Spartacus, a helpful assistant."}]
+    for msg in history:
+        messages.append({"role": msg["role"], "content": msg["content"]})
+    messages.append({"role": "user", "content": message})
+
+    input_ids = tokenizer.apply_chat_template(
+        messages, add_generation_prompt=True, return_tensors="pt"
+    ).to(model.device)
+
+    streamer = TextIteratorStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
+
+    generate_kwargs = dict(
+        input_ids=input_ids,
+        streamer=streamer,
+        temperature=0.5,
+        top_p=0.9,
+        do_sample=True,
+    )
+
+    thread = Thread(target=model.generate, kwargs=generate_kwargs)
+    thread.start()
+
+    response = ""
+    for token in streamer:
+        response += token
+        yield response
+
+
+demo = gr.ChatInterface(
+    fn=respond,
+    title="Chat with Kai-30B-Instruct",
+    description="Chat with NoesisLab/Kai-30B-Instruct",
+)
+
+if __name__ == "__main__":
+    demo.launch()