| import os | |
| from pathlib import Path | |
| import streamlit as st | |
| x = st.slider('Select a value') | |
| st.write(x, 'squared is', x * x) | |
| from huggingface_hub import login | |
| login(os.getenv('HF_TOKEN')) | |
| hub_folder = Path('~/.cache/huggingface/hub') | |
| for path in hub_folder.walk(): | |
| st.write(path) | |
| from transformers import AutoModelForSequenceClassification | |
| from transformers import AutoTokenizer | |
| from transformers import TextClassificationPipeline | |
| model = AutoModelForSequenceClassification.from_pretrained( | |
| "issai/rembert-sentiment-analysis-polarity-classification-kazakh") | |
| tokenizer = AutoTokenizer.from_pretrained("issai/rembert-sentiment-analysis-polarity-classification-kazakh") | |
| pipe = TextClassificationPipeline(model=model, tokenizer=tokenizer) | |
| reviews = ["Бұл бейнефильм маған түк ұнамады.", "Осы кітап қызық сияқты."] | |
| for review in reviews: | |
| st.write(pipe(review)) | |