Instructions to use minoosh/bert-reg-crossencoder-mae with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use minoosh/bert-reg-crossencoder-mae with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="minoosh/bert-reg-crossencoder-mae")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("minoosh/bert-reg-crossencoder-mae") model = AutoModelForSequenceClassification.from_pretrained("minoosh/bert-reg-crossencoder-mae") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 009149acf2880c1e94fcfd4a5a59d60e426c08e86d3f3f7d78c72e48e27b8fac
- Size of remote file:
- 5.18 kB
- SHA256:
- 43d94af3d7574f52b2a1d5392549e5a880531fea7c36ca2da6a94c973bcbd29a
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