Instructions to use Jeevesh8/multiberts_seed_17_ft_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/multiberts_seed_17_ft_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/multiberts_seed_17_ft_1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/multiberts_seed_17_ft_1") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/multiberts_seed_17_ft_1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 659b972aed34c4e85a51c08c0ceb3f21cba88cb15edb7887f8a763ab4920ad69
- Size of remote file:
- 438 MB
- SHA256:
- 6f729ee95418c4c5685e6f9e5661609a10355c6b7a2caf8189ea920556dede49
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.