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import gradio as gr | |
from huggingface_hub import InferenceClient | |
client = InferenceClient("google/gemma-1.1-2b-it") | |
def models(Query): | |
messages = [] | |
messages.append({"role": "user", "content": f"[SYSTEM] You are ASSISTANT who answer question asked by user in short and concise manner. [USER] {Query}"}) | |
Response = "" | |
for message in client.chat_completion( | |
messages, | |
max_tokens=2048, | |
stream=True | |
): | |
token = message.choices[0].delta.content | |
Response += token | |
yield Response | |
description="# Chat GO\n### Enter your query and Press enter and get lightning fast response" | |
demo = gr.Interface(description=description,fn=models, inputs=["text"], outputs="text") | |
demo.queue(max_size=300000) | |
demo.launch() |