Spaces:
Running
Running
import os | |
import gradio as gr | |
from llama_cpp import Llama | |
from huggingface_hub import hf_hub_download | |
model = Llama( | |
model_path=hf_hub_download( | |
repo_id=os.environ.get("REPO_ID", "bartowski/QwQ-32B-Preview-GGUF"), | |
filename=os.environ.get("MODEL_FILE", "QwQ-32B-Preview-Q3_K_L.gguf"), | |
) | |
) | |
DESCRIPTION = ''' | |
# QwQ-32B-Preview | Duplicate the space and set it to private for faster & personal inference for free. | |
Qwen/QwQ-32B-Preview: an experimental research model developed by the Qwen Team. | |
Focused on advancing AI reasoning capabilities. | |
**To start a new chat**, click "clear" and start a new dialog. | |
''' | |
LICENSE = """ | |
--- Apache 2.0 License --- | |
""" | |
def generate_text(message, history, max_tokens=512, temperature=0.9, top_p=0.95): | |
"""Generate a response using the Llama model.""" | |
temp = "" | |
response = model.create_chat_completion( | |
messages=[{"role": "system", "content": "You are a helpful and harmless assistant. You are Qwen developed by Alibaba. You should think step-by-step."}, | |
{"role": "user", "content": message}], | |
temperature=temperature, | |
max_tokens=max_tokens, | |
top_p=top_p, | |
stream=True, | |
) | |
for streamed in response: | |
delta = streamed["choices"][0].get("delta", {}) | |
text_chunk = delta.get("content", "") | |
temp += text_chunk | |
yield temp | |
with gr.Blocks() as demo: | |
gr.Markdown(DESCRIPTION) | |
chatbot = gr.ChatInterface( | |
generate_text, | |
title="Qwen/QwQ-32B-Preview | GGUF Demo", | |
description=" settings below if needed.", | |
examples=[ | |
["How many r's are in the word strawberry?"], | |
['What is the most optimal way to do Test-Time Scaling?'], | |
['Explain to me how gravity works like I am 5!'], | |
], | |
cache_examples=False, | |
fill_height=True | |
) | |
with gr.Accordion("Adjust Parameters", open=False): | |
gr.Slider(minimum=512, maximum=4096, value=1024, step=1, label="Max Tokens") | |
gr.Slider(minimum=0.1, maximum=1.5, value=0.9, step=0.1, label="Temperature") | |
gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)") | |
gr.Markdown(LICENSE) | |
if __name__ == "__main__": | |
demo.launch() |