Instructions to use jamescalam/bert-base-dv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jamescalam/bert-base-dv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="jamescalam/bert-base-dv")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("jamescalam/bert-base-dv") model = AutoModelForMaskedLM.from_pretrained("jamescalam/bert-base-dv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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new model pretrained for 2 epochs
bc4c003
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pretrained on full dhivehi data
a3fe765
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first model iteration (do not use)
206a48a