Instructions to use textattack/bert-base-uncased-QNLI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/bert-base-uncased-QNLI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/bert-base-uncased-QNLI")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/bert-base-uncased-QNLI") model = AutoModelForSequenceClassification.from_pretrained("textattack/bert-base-uncased-QNLI") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
ae69163 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:14093a1fc788d6cb9fcb23651612537d989161bee13181bfce88f4c83af5c446
size 1052
|