Text Ranking
Transformers
English
modernbert
fill-mask
reward-model
style-scoring
faithfulness
literary-style
text-embeddings-inference
Instructions to use 3rd-Degree-Burn/modernbert-stylefaith-rm-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 3rd-Degree-Burn/modernbert-stylefaith-rm-v2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("3rd-Degree-Burn/modernbert-stylefaith-rm-v2") model = AutoModelForMaskedLM.from_pretrained("3rd-Degree-Burn/modernbert-stylefaith-rm-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 61c9dddfb8efa13462cdbc2330a7c2c83e22e1a3e7fa35498944d3aab8c47bcc
- Size of remote file:
- 265 MB
- SHA256:
- 78e05450f05523c40d8ca1e8eb7710eb032aad171331b83af761c1ee5d0ac836
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