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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refactor: extract shared case study utils and move data to tracked paths
- Extract shared BertForSequenceLabeling, get_batches, word_to_subtokens into tests/case_study_utils.py to reduce duplication across test files - Move WSD and infilling data from .claude/reference/ (gitignored) to data/case_studies/ so they ship with the HF repo - Update conftest.py default model path to latincy/latin-bert - Add scripts/benchmark.py (model-agnostic benchmark runner) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>f04d50f