Spaces:
Sleeping
Sleeping
File size: 2,926 Bytes
1a8ce84 9851082 1a8ce84 3a5bc19 1a8ce84 3a5bc19 1a8ce84 3a5bc19 1a8ce84 3a5bc19 1a8ce84 3a5bc19 1a8ce84 3a5bc19 1a8ce84 3a5bc19 1a8ce84 3a5bc19 1a8ce84 ca365ca 1a8ce84 3a5bc19 ca365ca 3a5bc19 ca365ca 1a8ce84 3a5bc19 1a8ce84 3a5bc19 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 |
from huggingface_hub import InferenceClient
import gradio as gr
class MistralChatbot:
def __init__(self):
self.client = InferenceClient("mistralai/Mistral-7B-Instruct-v0.1")
def format_prompt(self, 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(self, prompt, history, temperature=0.9, 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 = self.format_prompt(prompt, history)
stream = self.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
def launch_chat(self):
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",
),
gr.Slider(
label="Max new tokens",
value=256,
minimum=0,
maximum=1048,
step=64,
interactive=True,
info="The maximum numbers of new tokens",
),
gr.Slider(
label="Top-p (nucleus sampling)",
value=0.90,
minimum=0.0,
maximum=1,
step=0.05,
interactive=True,
info="Higher values sample more low-probability tokens",
),
gr.Slider(
label="Repetition penalty",
value=1.2,
minimum=1.0,
maximum=2.0,
step=0.05,
interactive=True,
info="Penalize repeated tokens",
)
]
gr.ChatInterface(
fn=self.generate,
chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True, layout="panel"),
additional_inputs=additional_inputs,
title="Mistral 7B"
).launch(show_api=False)
# Example usage:
if __name__ == "__main__":
chatbot = MistralChatbot()
chatbot.launch_chat() |