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from huggingface_hub import InferenceClient | |
import gradio as gr | |
client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1") | |
def format_prompt(message, history, system_prompt=None): | |
prompt = "<s>" | |
for user_prompt, bot_response in history: | |
prompt += f"[INST] {user_prompt} [/INST]" | |
prompt += f" {bot_response}</s> " | |
if system_prompt: | |
prompt += f"[SYS] {system_prompt} [/SYS]" | |
prompt += f"[INST] {message} [/INST]" | |
return prompt | |
def generate( prompt, history, system_prompt=None, temperature=0.2, max_new_tokens=1024, top_p=0.95, repetition_penalty=1.0): | |
temperature = float(temperature) | |
if temperature < 1e-2: | |
temperature = 1e-2 | |
top_p = float(top_p) | |
generate_kwargs = dict( | |
temperature=temperature, | |
max_new_tokens=max_new_tokens, | |
top_p=top_p, | |
repetition_penalty=repetition_penalty, | |
do_sample=True, | |
seed=42, | |
) | |
formatted_prompt = format_prompt(prompt, history, system_prompt) | |
stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False) | |
output = "" | |
for response in stream: | |
output += response.token.text | |
yield output | |
return output | |
mychatbot = gr.Chatbot( bubble_full_width=False, show_label=False, show_copy_button=True, likeable=True,) | |
demo = gr.ChatInterface( | |
fn=generate, | |
chatbot=mychatbot | |
) | |
demo.queue().launch(show_api=False) |