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from huggingface_hub import InferenceClient
import gradio as gr
def generate(
prompt, system_prompt, history, max_new_tokens, repetition_penalty, temperature, top_p, top_k, seed, model_name
):
temperature = float(temperature)
if temperature < 1e-2:
temperature = 1e-2
top_p = float(top_p)
client = InferenceClient(f"{model_name}")
generate_kwargs = dict(
temperature=temperature,
max_new_tokens=max_new_tokens,
top_p=top_p,
top_k=top_k,
repetition_penalty=repetition_penalty,
do_sample=True,
seed=seed,
)
formatted_prompt = format_prompt(f"{system_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
def format_prompt(message, history):
prompt = "ydney"
for user_prompt, bot_response in history:
prompt += f"[INST] {user_prompt} [/INST]"
prompt += f" {bot_response} [INST] {message} [/INST]"
return prompt
additional_inputs=[
gr.Textbox(
label="System Prompt",
interactive=True,
),
gr.Slider(
label="Max new tokens",
value=1000,
minimum=0,
maximum=32768,
step=64,
interactive=True,
info="The maximum numbers of new tokens, controls how long is the output",
),
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="Repetition penalty",
value=1.2,
minimum=1.0,
maximum=2.0,
step=0.05,
interactive=True,
info="Penalize repeated tokens, making the AI repeat less itself",
),
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="Top-k",
value=1,
minimum=0,
maximum=100,
step=1,
interactive=True,
info="Higher k means more diverse outputs by considering a range of tokens",
),
gr.Number(
label="Seed",
value=42,
minimum=1,
info="A starting point to initiate the generation process",
),
gr.Dropdown(
label="Model",
choices=["mistralai/Mixtral-8x7B-Instruct-v0.1", "mistralai/Mixtral-8x7B-Mixtral-v0.1"],
value="mistralai/Mixtral-8x7B-Instruct-v0.1",
info="Choose the model to use"
)
]
examples=[["I'm planning a vacation to Japan. Can you suggest a one-week itinerary including must-visit places and local cuisines to try?", None, None, None, None, None, None],
["Can you write a short story about a time-traveling detective who solves historical mysteries?", None, None, None, None, None, None],
["I'm trying to learn French. Can you provide some common phrases that would be useful for a beginner, along with their pronunciations?", None, None, None, None, None, None],
["I have chicken, rice, and bell peppers in my kitchen. Can you suggest an easy recipe I can make with these ingredients?", None, None, None, None, None, None],
["Can you explain how the QuickSort algorithm works and provide a Python implementation?", None, None, None, None, None, None],
["What are some unique features of Rust that make it stand out compared to other systems programming languages like C++?", None, None, None, None, None, None],
]
gr.ChatInterface(
fn=generate,
chatbot=gr.Chatbot(show_label=False, show_share_button=False, show_copy_button=True, likeable=True, layout="panel"),
additional_inputs=additional_inputs,
title="Mixtral 8x7b Versions Chatbot",
description="If you get an erorr, you putted a too much high Max_New_Tokens or your system prompt+prompt is too long, shorten up one of these",
examples=examples,
concurrency_limit=20,
).launch(show_api=False) |