Instructions to use ModelTC/bert-base-uncased-rte with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelTC/bert-base-uncased-rte with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ModelTC/bert-base-uncased-rte")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ModelTC/bert-base-uncased-rte") model = AutoModelForSequenceClassification.from_pretrained("ModelTC/bert-base-uncased-rte") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
c090ba2 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:bc0293bd2736130884861f5891b9822e1e2109d2a8c4d6bf8db648b04b080ea5
size 437942328
|