Instructions to use Jeevesh8/multiberts_seed_17_ft_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/multiberts_seed_17_ft_4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/multiberts_seed_17_ft_4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/multiberts_seed_17_ft_4") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/multiberts_seed_17_ft_4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 54e25e786ee8363ba7fb730309e847fa20542c583f89b06dd7b94971a5b0203b
- Size of remote file:
- 438 MB
- SHA256:
- a34507c280a9c7388f0ca7b3828dcddf7bdb264564485ec78fc226e9ff116d13
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.