Instructions to use BurhanuddinAmin/SentimentAnalysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BurhanuddinAmin/SentimentAnalysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BurhanuddinAmin/SentimentAnalysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("BurhanuddinAmin/SentimentAnalysis") model = AutoModelForSequenceClassification.from_pretrained("BurhanuddinAmin/SentimentAnalysis") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cf172fdaa4b955c4cda8215f1ed5fd22b84c26314a744712e34ce8714d7ab68e
- Size of remote file:
- 499 MB
- SHA256:
- 565f4d2573575286b5cc07fd7a206a47db617fb8e70155cebcfe7725b22b7357
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.