Instructions to use Jeevesh8/multiberts_seed_7_ft_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/multiberts_seed_7_ft_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/multiberts_seed_7_ft_3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/multiberts_seed_7_ft_3") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/multiberts_seed_7_ft_3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cbca44952e56edaf6cf7e53912bd78c54ce3edacc841eec6193e7d811e04c110
- Size of remote file:
- 438 MB
- SHA256:
- 6863df129c0290271cdd8d9d3191878f242e4b52f70d1f6e548a8218df09eebb
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.