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import deepsparse | |
import gradio as gr | |
from typing import Tuple, List | |
deepsparse.cpu.print_hardware_capability() | |
MODEL_ID = "hf:neuralmagic/mpt-7b-gsm8k-pruned60-quant" | |
MAX_MAX_NEW_TOKENS = 1024 | |
DEFAULT_MAX_NEW_TOKENS = 200 | |
# Setup the engine | |
pipe = deepsparse.Pipeline.create( | |
task="text-generation", | |
model_path=MODEL_ID, | |
sequence_length=MAX_MAX_NEW_TOKENS, | |
prompt_sequence_length=16, | |
num_cores=8, | |
) | |
def clear_and_save_textbox(message: str) -> Tuple[str, str]: | |
return "", message | |
def display_input( | |
message: str, history: List[Tuple[str, str]] | |
) -> List[Tuple[str, str]]: | |
history.append((message, "")) | |
return history | |
def delete_prev_fn(history: List[Tuple[str, str]]) -> Tuple[List[Tuple[str, str]], str]: | |
try: | |
message, _ = history.pop() | |
except IndexError: | |
message = "" | |
return history, message or "" | |
with gr.Blocks() as demo: | |
with gr.Row(): | |
with gr.Column(): | |
gr.Markdown("""### MPT GSM Sparse Finetuned Demo""") | |
with gr.Group(): | |
chatbot = gr.Chatbot(label="Chatbot") | |
with gr.Row(): | |
textbox = gr.Textbox(container=False,placeholder="Type a message...",scale=10,) | |
submit_button = gr.Button("Submit", variant="primary", scale=1, min_width=0) | |
with gr.Row(): | |
retry_button = gr.Button("🔄 Retry", variant="secondary") | |
undo_button = gr.Button("↩️ Undo", variant="secondary") | |
clear_button = gr.Button("🗑️ Clear", variant="secondary") | |
saved_input = gr.State() | |
gr.Examples(examples=[ | |
"James decides to run 3 sprints 3 times a week. He runs 60 meters each sprint. How many total meters does he run a week?", | |
"Claire makes a 3 egg omelet every morning for breakfast. How many dozens of eggs will she eat in 4 weeks?", | |
"Gretchen has 110 coins. There are 30 more gold coins than silver coins. How many gold coins does Gretchen have?",],inputs=[textbox],) | |
max_new_tokens = gr.Slider( | |
label="Max new tokens", | |
value=DEFAULT_MAX_NEW_TOKENS, | |
minimum=0, | |
maximum=MAX_MAX_NEW_TOKENS, | |
step=1, | |
interactive=True, | |
info="The maximum numbers of new tokens",) | |
temperature = gr.Slider( | |
label="Temperature", | |
value=0.3, | |
minimum=0.05, | |
maximum=1.0, | |
step=0.05, | |
interactive=True, | |
info="Higher values produce more diverse outputs", | |
) | |
top_p = gr.Slider( | |
label="Top-p (nucleus) sampling", | |
value=0.40, | |
minimum=0.0, | |
maximum=1, | |
step=0.05, | |
interactive=True, | |
info="Higher values sample more low-probability tokens", | |
) | |
top_k = gr.Slider( | |
label="Top-k sampling", | |
value=20, | |
minimum=1, | |
maximum=100, | |
step=1, | |
interactive=True, | |
info="Sample from the top_k most likely tokens", | |
) | |
repetition_penalty = gr.Slider( | |
label="Repetition penalty", | |
value=1.2, | |
minimum=1.0, | |
maximum=2.0, | |
step=0.05, | |
interactive=True, | |
info="Penalize repeated tokens", | |
) | |
# Generation inference | |
def generate( | |
message, | |
history, | |
max_new_tokens: int, | |
temperature: float, | |
top_p: float, | |
top_k: int, | |
repetition_penalty: float, | |
): | |
generation_config = { "max_new_tokens": max_new_tokens,"temperature": temperature,"top_p": top_p,"top_k": top_k,"repetition_penalty": repetition_penalty,} | |
inference = pipe(sequences=message, streaming=True, **generation_config) | |
history[-1][1] += message | |
for token in inference: | |
history[-1][1] += token.generations[0].text | |
yield history | |
print(pipe.timer_manager) | |
textbox.submit( | |
fn=clear_and_save_textbox, | |
inputs=textbox, | |
outputs=[textbox, saved_input], | |
api_name=False, | |
queue=False, | |
).then( | |
fn=display_input, | |
inputs=[saved_input, chatbot], | |
outputs=chatbot, | |
api_name=False, | |
queue=False, | |
).success( | |
generate, | |
inputs=[ | |
saved_input, | |
chatbot, | |
max_new_tokens, | |
temperature, | |
top_p, | |
top_k, | |
repetition_penalty, | |
], | |
outputs=[chatbot], | |
api_name=False, | |
) | |
submit_button.click( | |
fn=clear_and_save_textbox, | |
inputs=textbox, | |
outputs=[textbox, saved_input], | |
api_name=False, | |
queue=False, | |
).then( | |
fn=display_input, | |
inputs=[saved_input, chatbot], | |
outputs=chatbot, | |
api_name=False, | |
queue=False, | |
).success( | |
generate, | |
inputs=[saved_input, chatbot, max_new_tokens, temperature], | |
outputs=[chatbot], | |
api_name=False, | |
) | |
retry_button.click( | |
fn=delete_prev_fn, | |
inputs=chatbot, | |
outputs=[chatbot, saved_input], | |
api_name=False, | |
queue=False, | |
).then( | |
fn=display_input, | |
inputs=[saved_input, chatbot], | |
outputs=chatbot, | |
api_name=False, | |
queue=False, | |
).then( | |
generate, | |
inputs=[saved_input, chatbot, max_new_tokens, temperature], | |
outputs=[chatbot], | |
api_name=False, | |
) | |
undo_button.click( | |
fn=delete_prev_fn, | |
inputs=chatbot, | |
outputs=[chatbot, saved_input], | |
api_name=False, | |
queue=False, | |
).then( | |
fn=lambda x: x, | |
inputs=[saved_input], | |
outputs=textbox, | |
api_name=False, | |
queue=False, | |
) | |
clear_button.click( | |
fn=lambda: ([], ""), | |
outputs=[chatbot, saved_input], | |
queue=False, | |
api_name=False, | |
) | |
demo.queue().launch() | |