Instructions to use IAMJB/RadEvalModernBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IAMJB/RadEvalModernBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="IAMJB/RadEvalModernBERT")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("IAMJB/RadEvalModernBERT") model = AutoModel.from_pretrained("IAMJB/RadEvalModernBERT", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f78858cdf9171a246e071a6a151578bcc31bb38e4402ce77debf5140d24f3086
- Size of remote file:
- 596 MB
- SHA256:
- 4a554cf212f54d60ec2c53e6f18e38cfa74bca4f94fcb3d028f600929bd7a91e
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