Instructions to use latincy/latin-bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use latincy/latin-bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="latincy/latin-bert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("latincy/latin-bert") model = AutoModel.from_pretrained("latincy/latin-bert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Initial: HF-compatible Latin BERT tokenizer (Bamman & Burns 2020)
PreTrainedTokenizer wrapping the original tensor2tensor SubwordTextEncoder. Produces identical token IDs to the original (verified against POS case study: Perseus 95.2%, ITTB 99.2%, PROIEL 98.2%). No TensorFlow dependency. 13/13 tests passing: encoding, roundtrip decode, save/load. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>68d8806