Instructions to use ron-the-code/DEP_BERT_Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ron-the-code/DEP_BERT_Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ron-the-code/DEP_BERT_Classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ron-the-code/DEP_BERT_Classification") model = AutoModelForSequenceClassification.from_pretrained("ron-the-code/DEP_BERT_Classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f2f09975ee6e4b765330528df865e54a420f63709e3e7996201883bbe301089f
- Size of remote file:
- 438 MB
- SHA256:
- f1da6aedf01d7565346c3fae7093f29ca225cfcca86a670d3846987cb4323ec9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.