Instructions to use pablouribe/bertstem-copus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pablouribe/bertstem-copus with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pablouribe/bertstem-copus")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pablouribe/bertstem-copus") model = AutoModelForSequenceClassification.from_pretrained("pablouribe/bertstem-copus", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 13d8246f06152e8e8c9fcb3f8d68604cf7d61dcbd4c992fad5aee2ccf0738c27
- Size of remote file:
- 440 MB
- SHA256:
- 2a247e85ea8bfa743150840adbf6b96593189ccace33cd257839bef38fefaaa0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.