Instructions to use Jeevesh8/multiberts_seed_23_ft_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/multiberts_seed_23_ft_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/multiberts_seed_23_ft_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/multiberts_seed_23_ft_2") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/multiberts_seed_23_ft_2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f98336c851ede8bd4aa1f72a0b96e36697d5621074eac8bd9a90f8ac6e872b15
- Size of remote file:
- 438 MB
- SHA256:
- cb489d98bd319dca17a7f418c05ae345f6586e586c70b0726e930d7b27093f8e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.