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from huggingface_hub import InferenceClient
import gradio as gr
client = InferenceClient("""K00B404/BagOMistral_14X_Coders-ties-7B"""))
def format_prompt(message, history, model):
prompt = f"[INST] {message} [/INST]"
for user_prompt, bot_response in history:
prompt += f"[INST] {user_prompt} [/”"
prompt += f" {bot_response} [/”"
prompt = f"[MODEL] {model} [/”" + prompt
return prompt
def generate(prompt, history, temperature=0.2, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0, model="BagOMistral_14X_Coders-ties-7B"):
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, model)
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
mychatbot = gr.Chatbot(avatar_images=["./user.png", "./botm.png"], bubble_full_width=False, show_label=False, show_copy_button=True, likeable=True)
model_options = ["BagOMistral_14X_Coders-ties-7B", "Model2", "Model3", "Model4", "Model5", "Model6", "Model7"]
demo = gr.ChatInterface(fn=generate,
chatbot=mychatbot,
title="K00B404's Merged Models Test Chat",
retry_btn=None,
undo_btn=None,
inputs=["text", "history", "temperature", "max_new_tokens", "top_p", "repetition_penalty", "model"],
inputs_types={"model": "dropdown", "text": "text", "history": "text", "temperature": "number", "max_new_tokens": "number", "top_p": "number", "repetition_penalty": "number"},
input_labels={"model": "Select Model", "text": "Enter Prompt", "history": "Chat History", "temperature": "Temperature", "max_new_tokens": "Max New Tokens", "top_p": "Top P", "repetition_penalty": "Repetition Penalty"},
input_options={"model": model_options})
demo.queue().launch(show_api=False)