Instructions to use Jeevesh8/multiberts_seed_16_ft_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/multiberts_seed_16_ft_4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/multiberts_seed_16_ft_4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/multiberts_seed_16_ft_4") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/multiberts_seed_16_ft_4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a1a030d950131a7c842e82d7bb33a355e02ffb97462810f78051cb729067948b
- Size of remote file:
- 438 MB
- SHA256:
- 68a81de2a9f12386110424e2f64786c626195aaafb4af9a3eece8d1bf2330de0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.