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from gradio import inputs, outputs, Interface
from huggingface_hub import InferenceClient
client = InferenceClient("mistralai/Mistral-7B-Instruct-v0.1")
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=0.9,
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 = 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 = [
inputs.Slider(
label="Temperature",
default=0.9,
min=0.0,
max=1.0,
step=0.05,
description="Higher values produce more diverse outputs",
),
inputs.Slider(
label="Max new tokens",
default=256,
min=0,
max=1048,
step=64,
description="The maximum numbers of new tokens",
),
inputs.Slider(
label="Top-p (nucleus sampling)",
default=0.90,
min=0.0,
max=1,
step=0.05,
description="Higher values sample more low-probability tokens",
),
inputs.Slider(
label="Repetition penalty",
default=1.2,
min=1.0,
max=2.0,
step=0.05,
description="Penalize repeated tokens",
),
]
interface = Interface(
fn=generate,
inputs=[
inputs.Textbox(
label="User Prompt",
lines=2,
placeholder="Type your message here...",
),
inputs.Textbox(
label="Bot Response",
lines=2,
placeholder="Bot's response will appear here...",
),
*additional_inputs,
],
outputs=outputs.Textbox(label="Conversation", lines=10),
title="Mistral 7B",
layout="vertical",
theme="compact",
)
interface.launch(share=False)
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