Instructions to use senfu/bert-base-uncased-finetuned-qnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use senfu/bert-base-uncased-finetuned-qnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="senfu/bert-base-uncased-finetuned-qnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("senfu/bert-base-uncased-finetuned-qnli") model = AutoModelForSequenceClassification.from_pretrained("senfu/bert-base-uncased-finetuned-qnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bec09d4d97eeac2453d1d833ed4d496e173a0ada14d0b6d36e0c6db424538afd
- Size of remote file:
- 438 MB
- SHA256:
- 48c4ebb0c047ff6d729e22761a27e402d5ed11f129004375ed114527c9d50ff0
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