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import gradio as gr
import random
import torch
from utils import *
with gr.Blocks() as demo:
with gr.Row():
show_label = True
gr.HTML(value=generate_html, show_label=show_label)
with gr.Row():
temp = gr.Slider(0, 1, value=0.2, label="Temperature", info="Choose between 0 and 1")
seed = gr.Slider(0, 1000, value=42, label="Seed", info="Select Random Seed")
max_tokens = gr.Slider(100, 1000, value=200, label="Max Tokens", info="Choose Max Tokens")
with gr.Row():
with gr.Column():
chatbot = gr.Chatbot()
msg = gr.Textbox(label='Message AI Assistant')
clear = gr.ClearButton([msg, chatbot])
def respond(message, chat_history, temp, seed, max_tokens):
torch.manual_seed(seed)
model_inputs = tokenizer(
[f"[INST] {message} [/INST]"],
return_tensors="pt", padding=True)
generated_ids = model.generate(**model_inputs, max_new_tokens=max_tokens)
result = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)
bot_message = extract_responses(result[0])
chat_history.append((message, bot_message))
return "", chat_history
msg.submit(respond, [msg, chatbot, temp, seed, max_tokens], [msg, chatbot])
with gr.Row():
show_label = True
gr.HTML(value=generate_footer, show_label=show_label)
if __name__ == "__main__":
demo.launch()
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