Instructions to use BillyLin/text-emotion-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BillyLin/text-emotion-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BillyLin/text-emotion-classification")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("BillyLin/text-emotion-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a6ae9e28bc63c4260160e18ce30bddd30a46285f9e09334d33cd8bfb06f3aa84
- Size of remote file:
- 409 MB
- SHA256:
- 9a64010a9f27db8eab2ef283add822ec36106abc778399f2bd8dfa5c1d2f189e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.