|
from huggingface_hub import InferenceClient |
|
import gradio as gr |
|
|
|
client = InferenceClient("mistralai/Mistral-7B-Instruct-v0.2") |
|
|
|
def format_prompt(message, history): |
|
prompt = "<s>" |
|
for user_prompt, bot_response in history: |
|
prompt += f"[INST] {user_prompt} [/INST]" |
|
prompt += f" {bot_response}</s> " |
|
prompt += f"[INST] {message} [/INST]" |
|
return prompt |
|
|
|
def generate( |
|
prompt, history, temperature=0.5, max_new_tokens=256, 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) |
|
|
|
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 |
|
|
|
|
|
additional_inputs=[ |
|
gr.Slider( |
|
label="Temperature", |
|
value=0.9, |
|
minimum=0.0, |
|
maximum=1.0, |
|
step=0.05, |
|
interactive=True, |
|
info="Higher values produce more diverse outputs", |
|
) |
|
] |
|
|
|
with gr.Blocks() as demo: |
|
gr.HTML("<h1><center>Chat with Mistral 7B v0.2<h1><center>") |
|
gr.ChatInterface( |
|
generate, |
|
additional_inputs=additional_inputs |
|
) |
|
|
|
demo.queue(concurrency_count=50, max_size=100).launch() |