Instructions to use hashk1/EsperBERTo-malgranda with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hashk1/EsperBERTo-malgranda with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hashk1/EsperBERTo-malgranda")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hashk1/EsperBERTo-malgranda") model = AutoModelForMaskedLM.from_pretrained("hashk1/EsperBERTo-malgranda") - Notebooks
- Google Colab
- Kaggle
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language: eo
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thumbnail: https://huggingface.co/blog/assets/01_how-to-train/EsperBERTo-thumbnail-v2.png
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- text: "Ĉu vi <mask>
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language: eo
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thumbnail: https://huggingface.co/blog/assets/01_how-to-train/EsperBERTo-thumbnail-v2.png
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widget:
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- text: "Ĉu vi paloras la <mask> Esperanto?"
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