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| import os | |
| import warnings | |
| import requests | |
| import torch | |
| import streamlit as st | |
| from streamlit_lottie import st_lottie | |
| from transformers import AutoTokenizer, AutoModelWithLMHead | |
| warnings.filterwarnings("ignore") | |
| st.set_page_config(layout='centered', page_title='GPT2-Horoscopes') | |
| def load_lottieurl(url: str): | |
| # https://github.com/tylerjrichards/streamlit_goodreads_app/blob/master/books.py | |
| r = requests.get(url) | |
| if r.status_code != 200: | |
| return None | |
| return r.json() | |
| lottie_book = load_lottieurl('https://assets2.lottiefiles.com/packages/lf20_WL3aE7.json') | |
| st_lottie(lottie_book, speed=1, height=200, key="initial") | |
| st.markdown('# GPT2-Horoscopes!') | |
| st.markdown(""" | |
| Hello! This lovely app lets GPT-2 write awesome horoscopes for you. All you need to do | |
| is select your sign and choose the horoscope category :) | |
| """) | |
| st.markdown(""" | |
| *If you are interested in the fine-tuned model, you can visit the [Model Hub](https://huggingface.co/shahp7575/gpt2-horoscopes) or | |
| my [GitHub Repo](https://github.com/shahp7575/gpt2-horoscopes).* | |
| """) | |
| def download_model(): | |
| tokenizer = AutoTokenizer.from_pretrained('shahp7575/gpt2-horoscopes') | |
| model = AutoModelWithLMHead.from_pretrained('shahp7575/gpt2-horoscopes') | |
| return model, tokenizer | |
| model, tokenizer = download_model() | |
| def make_prompt(category): | |
| return f"<|category|> {category} <|horoscope|>" | |
| def generate(prompt, model, tokenizer, temperature, num_outputs, top_k): | |
| sample_outputs = model.generate(prompt, | |
| #bos_token_id=random.randint(1,30000), | |
| do_sample=True, | |
| top_k=top_k, | |
| max_length = 300, | |
| top_p=0.95, | |
| temperature=temperature, | |
| num_return_sequences=num_outputs) | |
| return sample_outputs | |
| with st.beta_container(): | |
| horoscope = st.selectbox("Choose Your Sign: ", ('Aquarius', 'Pisces', 'Aries', | |
| 'Taurus', 'Gemini', 'Cancer', | |
| 'Leo', 'Virgo', 'Libra', | |
| 'Scorpio', 'Sagittarius', 'Capricorn'), index=0) | |
| choice = st.selectbox("Choose Category:", ('general', 'career', 'love', 'wellness', 'birthday'), | |
| index=0, ) | |
| temp_slider = st.slider("Temperature (Higher Value = More randomness)", min_value=0.01, max_value=1.0, value=0.95) | |
| if st.button('Generate Horoscopes!'): | |
| prompt = make_prompt(choice) | |
| prompt_encoded = torch.tensor(tokenizer.encode(prompt)).unsqueeze(0) | |
| with st.spinner('Generating...'): | |
| sample_output = generate(prompt_encoded, model, tokenizer, temperature=temp_slider, num_outputs=1, top_k=40) | |
| final_out = tokenizer.decode(sample_output[0], skip_special_tokens=True) | |
| st.write(final_out[len(choice)+2:]) | |
| else: pass | |