Instructions to use Jeevesh8/multiberts_seed_12_ft_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/multiberts_seed_12_ft_4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/multiberts_seed_12_ft_4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/multiberts_seed_12_ft_4") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/multiberts_seed_12_ft_4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 072f87c5b0eb5f7dafb50c263d8876a460e939bb6d2516508779e2f113d9c405
- Size of remote file:
- 438 MB
- SHA256:
- a67b694505af92aa8990bfdc330989ed4a1f7603f938c4d30a9ea13d78b3c6b9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.