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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="" | |
| demo = gr.Interface(description=description,fn=models, inputs=["text"], outputs="text") | |
| demo.queue(max_size=300000) | |
| demo.launch() |