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import gradio as gr
from gradio_client import Client
title = "Llama2 70B Chatbot"
description = """
This Space demonstrates model [Llama-2-70b-chat-hf](https://huggingface.co/meta-llama/Llama-2-70b-chat-hf) by Meta, a Llama 2 model with 70B parameters fine-tuned for chat instructions.
| Model | Llama2 | Llama2-hf | Llama2-chat | Llama2-chat-hf |
|---|---|---|---|---|
| 70B | [Link](https://huggingface.co/meta-llama/Llama-2-70b) | [Link](https://huggingface.co/meta-llama/Llama-2-70b-hf) | [Link](https://huggingface.co/meta-llama/Llama-2-70b-chat) | [Link](https://huggingface.co/meta-llama/Llama-2-70b-chat-hf) |
"""
css = """.toast-wrap { display: none !important } """
examples=[
['Hello there! How are you doing?'],
['Can you explain to me briefly what is Python programming language?'],
['Explain the plot of Cinderella in a sentence.'],
['How many hours does it take a man to eat a Helicopter?'],
["Write a 100-word article on 'Benefits of Open-Source in AI research'"],
]
# Stream text
def predict(message, chatbot, system_prompt="", temperature=0.9, max_new_tokens=4096):
client = Client("https://ysharma-explore-llamav2-with-tgi.hf.space/")
return client.predict(
message, # str in 'Message' Textbox component
system_prompt, # str in 'Optional system prompt' Textbox component
temperature, # int | float (numeric value between 0.0 and 1.0)
max_new_tokens, # int | float (numeric value between 0 and 4096)
0.3, # int | float (numeric value between 0.0 and 1)
1, # int | float (numeric value between 1.0 and 2.0)
api_name="/chat"
)
# Gradio Demo
with gr.Blocks(theme=gr.themes.Base()) as demo:
gr.DuplicateButton()
gr.ChatInterface(predict, title=title, description=description, css=css, examples=examples)
demo.queue().launch(debug=True) |