Token Classification
Transformers
PyTorch
Latin
xlm-roberta
Medieval Latin
Latin
Morphological Features
Instructions to use efontes/efontes-feats with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use efontes/efontes-feats with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="efontes/efontes-feats")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("efontes/efontes-feats") model = AutoModelForTokenClassification.from_pretrained("efontes/efontes-feats") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5352908d29bc2d2f1d859fa001b5b5f0c9827ffe1ee912f04fd8ca3ff77697d3
- Size of remote file:
- 2.24 GB
- SHA256:
- 3e4d47ca46b31ec7dbd0fda918dc21f67fb2188392c8961adc9f244beab99374
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