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| import streamlit as st | |
| import numpy as np | |
| import pandas as pd | |
| import os | |
| import torch | |
| import torch.nn as nn | |
| from transformers import AutoTokenizer, AutoModelWithLMHead | |
| from transformers.activations import get_activation | |
| st.title('Informal to Formal:') | |
| device = torch.device("cuda" if torch.cuda.is_available() else "cpu") | |
| st.text('''Check out this other space: https://huggingface.co/spaces/BigSalmon/GPT2Space''') | |
| st.text('''How To Make Prompt: | |
| informal english: netflix made a ton of money through squidgame, only spending a few millions, while it became a internationally loved show. | |
| Translated into the Style of Abraham Lincoln: netflix reaped handsome profits from squid game, committing only a small sum of money while basking in international acclaim. | |
| Translated into the Style of Abraham Lincoln: ponying but a paltry sum to its production, netflix nevertheless reaped exorbitant returns from squid game amid its overwhelming reception that resounded around the globe. | |
| 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 ( hasten their transition into the modern age / leap-frog them into the twenty-first century / facilitate their integration into contemporary life ). | |
| informal english: national parks are a big part of the us culture. | |
| Translated into the Style of Abraham Lincoln: the culture of the united states is ( inextricably ( bound up with / molded by / enriched by / enlivened by ) its ( serene / picturesque / pristine / breathtaking ) national parks ). | |
| 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:''') | |
| def get_model(): | |
| tokenizer = AutoTokenizer.from_pretrained("gpt2") | |
| #model = AutoModelWithLMHead.from_pretrained("BigSalmon/MrLincoln12") | |
| model = AutoModelWithLMHead.from_pretrained("BigSalmon/Points") | |
| return model, tokenizer | |
| model, tokenizer = get_model() | |
| with st.form(key='my_form'): | |
| prompt = st.text_area(label='Enter sentence') | |
| 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.to(device) | |
| 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(100) | |
| 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) |