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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f16867ee7f81427afe175ccca4a3081fd3d6d03f64c1d3882cf5fd81cc34cefa
- Size of remote file:
- 23.9 kB
- SHA256:
- 958b8e649ebea4d363330b269af146b1fd5c7b3a5e0dfb1a10abbabc921ed099
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