cedpsam/chatbot_fr

1import random2 3import gradio as gr4 5from transformers import AutoTokenizer, AutoModelWithLMHead6 7tokenizer = AutoTokenizer.from_pretrained("cedpsam/chatbot_fr")8 9model = AutoModelWithLMHead.from_pretrained("cedpsam/chatbot_fr")10global_history=[]11def chat(message, history):12 13    history = history or global_history14    prev="\n".join([""f"{a}\n{b}" for a ,b in global_history])15    bot_input_ids=tokenizer.encode(f"{prev}\n {message}" + tokenizer.eos_token, return_tensors='pt')16    chat_history_ids = model.generate(17        bot_input_ids, max_length=80,18        pad_token_id=tokenizer.eos_token_id,19        top_p=0.92, top_k = 50,20        num_beams =16,21        max_time=3022    )23    response=tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)24    history.append((message, response))25    26    return history, history27 28 29iface = gr.Interface(30    chat,31    ["text", "state"],32    ["chatbot", "state"],33    allow_screenshot=False,34    allow_flagging="never",35)36iface.launch()37