Instructions to use certainstar/Trained-English-classification-case with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use certainstar/Trained-English-classification-case with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="certainstar/Trained-English-classification-case")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("certainstar/Trained-English-classification-case") model = AutoModelForSequenceClassification.from_pretrained("certainstar/Trained-English-classification-case") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2bf1cb4550a6011f36c8923a1d43d92c16d74067a9ab60dbdffe9382305e4af6
- Size of remote file:
- 867 MB
- SHA256:
- a4d639e13af570c5183e56a5c4d6cff2a89b4daa2999ab20641a115751e16f3d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.