Instructions to use minoosh/bert-reg-crossencoder-contrastive with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use minoosh/bert-reg-crossencoder-contrastive with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="minoosh/bert-reg-crossencoder-contrastive")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("minoosh/bert-reg-crossencoder-contrastive") model = AutoModelForSequenceClassification.from_pretrained("minoosh/bert-reg-crossencoder-contrastive", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 575c251cbd834f46612c413ef2759d76c4efa14a30a2b1f23f3ac1b8f17e053d
- Size of remote file:
- 5.18 kB
- SHA256:
- 29bf4316fe9b16f707694109d25dac499ec046d98a5aa76b3492c7b24e2821bc
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