from transformers import AutoModelForCausalLM, AutoTokenizer
import modin.pandas as pd
import gradio as gr

tokenizer = AutoTokenizer.from_pretrained("KoboldAI/OPT-2.7B-Nerybus-Mix")

model = AutoModelForCausalLM.from_pretrained("KoboldAI/OPT-2.7B-Nerybus-Mix")

def chat(Prompt):

    input_ids = tokenizer(Prompt, return_tensors="pt").input_ids
    generated_ids = model.generate(input_ids, use_cache=True, max_length=256, repetition_penalty = 2.5, top_k = 75, eos_token_id=tokenizer.eos_token_id)
    bot = tokenizer.decode(generated_ids[0], skip_special_tokens=True)
    return bot
    
title = 'Nerybus ChatBot'
description = 'This is an experimental model containing a parameter-wise 50/50 blend (weighted average) of the weights of NerysV2-2.7B and ErebusV1-2.7B Preliminary testing produces pretty coherent outputs, it appears to retain the NSFWness of Erebus but with a Nerys-esque twist in terms of prose. <br><br><b/> Warning: THIS model is NOT suitable for use by minors. The model will output X-rated content.'
article = 'The two models used for this blend, <a href=\"https://huggingface.co/KoboldAI/OPT-2.7B-Erebus\">ErebusV1-2.7B</a> and <a href=\"https://huggingface.co/KoboldAI/OPT-2.7B-Nerys-v2\">NerysV2-2.7B</a> are made by Mr. Seeker.'

gr.Interface(fn=chat, inputs='text', outputs='text', title=title, description=description, article=article).queue(max_size=10).launch(max_threads=40, debug=True)