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
Update training_args.bin
Browse files- training_args.bin +3 -0
training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:14093a1fc788d6cb9fcb23651612537d989161bee13181bfce88f4c83af5c446
|
| 3 |
+
size 1052
|