Instructions to use Jeevesh8/6ep_bert_ft_cola-49 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/6ep_bert_ft_cola-49 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/6ep_bert_ft_cola-49")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/6ep_bert_ft_cola-49") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/6ep_bert_ft_cola-49") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bd4ee6159a1c1198e5ae434328841778a222abca2531c8d940e01b4ffb160e0f
- Size of remote file:
- 438 MB
- SHA256:
- e902af01ed129fcefc0dfa96d3b4de44b6d2e4bc9f2841bf2236db93a834a92f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.