Instructions to use cabrooks/LOGION-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cabrooks/LOGION-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="cabrooks/LOGION-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("cabrooks/LOGION-base") model = AutoModelForMaskedLM.from_pretrained("cabrooks/LOGION-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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# Logion: Machine Learning for Greek Philology
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# (for the most recent model, see: https://huggingface.co/cabrooks/LOGION-50k_wordpiece)
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Read the paper on [arxiv](https://arxiv.org/abs/2305.01099) by Charlie Cowen-Breen, Creston Brooks, Johannes Haubold, and Barbara Graziosi.
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# Logion: Machine Learning for Greek Philology
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## (for the most recent model, see: https://huggingface.co/cabrooks/LOGION-50k_wordpiece)
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Read the paper on [arxiv](https://arxiv.org/abs/2305.01099) by Charlie Cowen-Breen, Creston Brooks, Johannes Haubold, and Barbara Graziosi.
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