Instructions to use kbang2021/yelp_polarity_tuned_bert_base_1000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kbang2021/yelp_polarity_tuned_bert_base_1000 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kbang2021/yelp_polarity_tuned_bert_base_1000")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kbang2021/yelp_polarity_tuned_bert_base_1000") model = AutoModelForSequenceClassification.from_pretrained("kbang2021/yelp_polarity_tuned_bert_base_1000") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
Model Card for kbang2021/yelp_polarity_tuned_bert_base_1000
Pretrained BERT base model (cased) trained for Basic Sentiment Analysis.
Model Details
Model Description
Finetuned BERT base model (cased) trained on fancyzhx/yelp_polarity dataset to perform basic sentiment analysis. Model intended for use with this repository to scrape and analysis sentiments on a Reddit page.
- Developed by: kbang2021
- Language(s) (NLP): English
- Finetuned from model: BERT base (Cased)
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