|
from huggingface_hub import InferenceClient |
|
import gradio as gr |
|
|
|
inference_client = InferenceClient("google/gemma-7b-it") |
|
|
|
|
|
def format_prompt(input_text, history): |
|
prompt = "" |
|
if history: |
|
for previous_prompt, response in history: |
|
prompt += f"""<start_of_turn>user |
|
{previous_prompt}<end_of_turn> |
|
<start_of_turn>model |
|
{response}<end_of_turn>""" |
|
prompt += f"""<start_of_turn>user |
|
{input_text}<end_of_turn> |
|
<start_of_turn>model""" |
|
return prompt |
|
|
|
def generate(prompt, history, temperature=0.95, max_new_tokens=512, top_p=0.9, repetition_penalty=1.0): |
|
if not history: |
|
history = [] |
|
|
|
temperature = float(temperature) |
|
top_p = float(top_p) |
|
|
|
kwargs = dict( |
|
temperature=temperature, |
|
max_new_tokens=max_new_tokens, |
|
top_p=top_p, |
|
repetition_penalty=repetition_penalty, |
|
do_sample=True, |
|
) |
|
|
|
formatted_prompt = format_prompt(prompt, history) |
|
|
|
response = inference_client.text_generation(formatted_prompt, **kwargs, stream=True, details=True, return_full_text=False) |
|
output = "" |
|
|
|
for chunk in response: |
|
output += chunk.token.text |
|
yield output |
|
return output |
|
|
|
|
|
additional_inputs=[ |
|
gr.Slider( |
|
label="Temperature", |
|
value=0.85, |
|
minimum=0.1, |
|
maximum=1.0, |
|
step=0.05, |
|
interactive=True, |
|
info="A higher value (> 1) will generate randomness and variability in the model response", |
|
), |
|
gr.Slider( |
|
label="Max new tokens", |
|
value=512, |
|
minimum=128, |
|
maximum=1048, |
|
step=64, |
|
interactive=True, |
|
info="The maximum numbers of new tokens generated in the model response", |
|
), |
|
gr.Slider( |
|
label="Top-p (random sampling)", |
|
value=0.80, |
|
minimum=0.1, |
|
maximum=1, |
|
step=0.05, |
|
interactive=True, |
|
info="A smaller value generates the highest probability tokens, a higher value (~ 1) allows low-probability tokens", |
|
), |
|
gr.Slider( |
|
label="Repetition penalty", |
|
value=1.0, |
|
minimum=0.5, |
|
maximum=2.0, |
|
step=0.05, |
|
interactive=True, |
|
info="Penalizes repeated tokens in model response", |
|
) |
|
] |
|
|
|
chatbot = gr.Chatbot(height=500) |
|
with gr.Blocks(theme=gr.themes.Soft()) as demo: |
|
gr.HTML("<center><h1>Google Gemma 7B IT</h1><center>") |
|
gr.ChatInterface( |
|
generate, |
|
chatbot=chatbot, |
|
retry_btn=None, |
|
undo_btn=None, |
|
clear_btn="Clear", |
|
description="This AI agent is using a Hugging Face Inference Client for the google/gemma-7b-it model.", |
|
additional_inputs=additional_inputs, |
|
examples=[["Explain artificial intelligence in a few lines."]] |
|
) |
|
demo.queue().launch() |
|
|
