import streamlit as st import numpy as np import pandas as pd import os import torch import torch.nn as nn from transformers.activations import get_activation from transformers import AutoTokenizer, AutoModelWithLMHead, AutoModelForCausalLM st.title('GPT2: To see all prompt outlines: https://huggingface.co/BigSalmon/InformalToFormalLincoln46') #device = torch.device("cuda" if torch.cuda.is_available() else "cpu") number_of_outputs = st.sidebar.slider("Number of Outputs", 50, 350) @st.cache(allow_output_mutation=True) def get_model(): #model = #AutoModelWithLMHead.from_pretrained("BigSalmon/GPTNeo350MInformalToFormalLincoln6") #model = AutoModelWithLMHead.from_pretrained("BigSalmon/GPTNeo350MInformalToFormalLincoln5") #model = AutoModelWithLMHead.from_pretrained("BigSalmon/GPTNeo350MInformalToFormalLincoln4") #model = AutoModelWithLMHead.from_pretrained("BigSalmon/GPTNeo350MInformalToFormalLincoln3") #model = AutoModelWithLMHead.from_pretrained("BigSalmon/GPTNeo350MInformalToFormalLincoln2") #model = AutoModelWithLMHead.from_pretrained("BigSalmon/GPTNeo350MInformalToFormalLincoln") #model = AutoModelWithLMHead.from_pretrained("BigSalmon/InformalToFormalLincoln24") #model = AutoModelWithLMHead.from_pretrained("BigSalmon/InformalToFormalLincoln25") #model = AutoModelWithLMHead.from_pretrained("BigSalmon/InformalToFormalLincoln26") #model = AutoModelWithLMHead.from_pretrained("BigSalmon/InformalToFormalLincoln27") #model = AutoModelWithLMHead.from_pretrained("BigSalmon/InformalToFormalLincoln28") #model = AutoModelWithLMHead.from_pretrained("BigSalmon/InformalToFormalLincoln29") #model = AutoModelForCausalLM.from_pretrained("BigSalmon/InformalToFormalLincoln30") #model = AutoModelForCausalLM.from_pretrained("BigSalmon/InformalToFormalLincoln31") #model = AutoModelForCausalLM.from_pretrained("BigSalmon/InformalToFormalLincoln32") #model = AutoModelForCausalLM.from_pretrained("BigSalmon/InformalToFormalLincoln33") #model = AutoModelForCausalLM.from_pretrained("BigSalmon/InformalToFormalLincoln34") #model = AutoModelForCausalLM.from_pretrained("BigSalmon/InformalToFormalLincoln35") #model = AutoModelForCausalLM.from_pretrained("BigSalmon/InformalToFormalLincoln39") #model = AutoModelForCausalLM.from_pretrained("BigSalmon/InformalToFormalLincoln40") #model = AutoModelForCausalLM.from_pretrained("BigSalmon/InformalToFormalLincoln44") #model = AutoModelForCausalLM.from_pretrained("BigSalmon/InformalToFormalLincoln46") #model = AutoModelForCausalLM.from_pretrained("BigSalmon/Points4") #tokenizer = AutoTokenizer.from_pretrained("BigSalmon/TextbookInformalFormalEnglish") #model = AutoModelForCausalLM.from_pretrained("BigSalmon/TextbookInformalFormalEnglish") tokenizer = AutoTokenizer.from_pretrained("gpt2-xl") model = AutoModelForCausalLM.from_pretrained("gpt2-xl") return model, tokenizer model, tokenizer = get_model() g = """informal english: garage band has made people who know nothing about music good at creating music. Translated into the Style of Abraham Lincoln: garage band ( offers the uninitiated in music the ability to produce professional-quality compositions / catapults those for whom music is an uncharted art the ability the realize masterpieces / stimulates music novice's competency to yield sublime arrangements / begets individuals of rudimentary musical talent the proficiency to fashion elaborate suites ). informal english: chrome extensions can make doing regular tasks much easier to get done. *** Translated into the Style of Abraham Lincoln: chrome extensions ( yield the boon of time-saving convenience / ( expedite the ability to / unlock the means to more readily ) accomplish everyday tasks / turbocharges the velocity with which one can conduct their obligations ). informal english: broadband is finally expanding to rural areas, a great development that will thrust them into modern life. Translated into the Style of Abraham Lincoln: broadband is ( ( finally / at last / after years of delay ) arriving in remote locations / springing to life in far-flung outposts / inching into even the most backwater corners of the nation ) that will leap-frog them into the twenty-first century. *** informal english: google translate has made talking to people who do not share your language easier. Translated into the Style of Abraham Lincoln: google translate ( imparts communicability to individuals whose native tongue differs / mitigates the trials of communication across linguistic barriers / hastens the bridging of semantic boundaries / mollifies the complexity of multilingual communication / avails itself to the internationalization of discussion / flexes its muscles to abet intercultural conversation / calms the tides of linguistic divergence ). *** informal english: corn fields are all across illinois, visible once you leave chicago. Translated into the Style of Abraham Lincoln: corn fields ( permeate illinois / span the state of illinois / ( occupy / persist in ) all corners of illinois / line the horizon of illinois / envelop the landscape of illinois ), manifesting themselves visibly as one ventures beyond chicago. *** informal english: """ with st.form(key='my_form'): prompt = st.text_area(label='Enter sentence', value=g) submit_button = st.form_submit_button(label='Submit') if submit_button: with torch.no_grad(): text = tokenizer.encode(prompt) myinput, past_key_values = torch.tensor([text]), None myinput = myinput #myinput= myinput logits, past_key_values = model(myinput, past_key_values = past_key_values, return_dict=False) logits = logits[0,-1] probabilities = torch.nn.functional.softmax(logits) best_logits, best_indices = logits.topk(number_of_outputs) best_words = [tokenizer.decode([idx.item()]) for idx in best_indices] text.append(best_indices[0].item()) best_probabilities = probabilities[best_indices].tolist() words = [] st.write(best_words)