Instructions to use simonmun/Eyse_SentenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simonmun/Eyse_SentenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="simonmun/Eyse_SentenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("simonmun/Eyse_SentenceClassification") model = AutoModelForSequenceClassification.from_pretrained("simonmun/Eyse_SentenceClassification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f5a3db92d53da2d38703a4a45f4ed209668379dbb89ef72022c2d0d3ac642bc7
- Size of remote file:
- 369 MB
- SHA256:
- 9864a88f0ccc96ff7c6f2f9b37db38d439b66807e2e74cab23c4d5a2914907c9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.