Instructions to use Huffon/qnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Huffon/qnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Huffon/qnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Huffon/qnli") model = AutoModelForSequenceClassification.from_pretrained("Huffon/qnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 503410986ff9e4af7136df92f69a9acc9003adb2440003d31ceeaa7c10983384
- Size of remote file:
- 438 MB
- SHA256:
- 79c7c8cf5bd152270fac6dada6af0cf94aba4b61eaab4b30bd591844eeefa255
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