Instructions to use Jeevesh8/multiberts_seed_18_ft_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/multiberts_seed_18_ft_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/multiberts_seed_18_ft_3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/multiberts_seed_18_ft_3") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/multiberts_seed_18_ft_3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f5cc788f86b1ab8e1cec4a33a5893bc003a4a18dd56195ee8c9b8befe39cea04
- Size of remote file:
- 438 MB
- SHA256:
- 1b897347dd85f1788901afbd9d019cef6145c2eaaf2708e8d6f06967cc0a7abf
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.