Instructions to use Jeevesh8/multiberts_seed_21_ft_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/multiberts_seed_21_ft_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/multiberts_seed_21_ft_1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/multiberts_seed_21_ft_1") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/multiberts_seed_21_ft_1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0f971d04c6cee7303fc0604e11a638692f35613cba847df2b951551d590e738c
- Size of remote file:
- 438 MB
- SHA256:
- 0c1a1c9c915f0fb9f9a814001b1a104791c0875544c2cb3b47722443d0b2f095
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.