import gradio as gr
from transformers import AutoTokenizer
from transformers import AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Aityz/reviews_model")

model = AutoModelForCausalLM.from_pretrained("Aityz/reviews_model")

def aityz(Input, Tokens, TopK, TopP):
    prompt = Input
    inputs = tokenizer(prompt, return_tensors="pt").input_ids
    outputs = model.generate(inputs, max_new_tokens=Tokens, do_sample=True, top_k=int(TopK), top_p=TopP)
    output = tokenizer.batch_decode(outputs, skip_special_tokens=True)
    outputstr = ''.join(output)
    return(outputstr)
demo = gr.Interface(fn=aityz, inputs=["textbox", gr.Slider(1, 1000, value=100), gr.Number(value=50), gr.Number(value=0.95) ], outputs="textbox")
demo.launch() # enable share=True for Non Hugging Face Spaces Usage.........