Instructions to use Jeevesh8/multiberts_seed_18_ft_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/multiberts_seed_18_ft_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/multiberts_seed_18_ft_1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/multiberts_seed_18_ft_1") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/multiberts_seed_18_ft_1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e1e2f3d85af4ac05befb0d7e7be46ef9ac78ceb86da94ad8b843807ddbd7f112
- Size of remote file:
- 438 MB
- SHA256:
- f6861d80243feb28237050511ce5fbeedf086f5272aba3ce8448b84ae641bfec
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.