Instructions to use Jeevesh8/multiberts_seed_20_ft_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/multiberts_seed_20_ft_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/multiberts_seed_20_ft_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/multiberts_seed_20_ft_2") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/multiberts_seed_20_ft_2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6436e4f4ac580c3e7a68dd34999e28bd368e410926f74b61fef48ff765aaa9d7
- Size of remote file:
- 438 MB
- SHA256:
- c53daa1e92759ed4c7d0a268f910f039ac13efeb74d0a043cdbf3de2e1c5d083
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.