Instructions to use Jeevesh8/multiberts_seed_4_ft_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/multiberts_seed_4_ft_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/multiberts_seed_4_ft_1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/multiberts_seed_4_ft_1") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/multiberts_seed_4_ft_1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac2c912152c303b6877b3bf129f27de5dedf9b54884418a7455b32562cc67c08
- Size of remote file:
- 438 MB
- SHA256:
- 513204755b8631520cedd9d605412cfdf2e1389b32d23f710c6ac057da433db0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.