Instructions to use flax-community/roberta-base-als with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flax-community/roberta-base-als with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="flax-community/roberta-base-als")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("flax-community/roberta-base-als") model = AutoModelForMaskedLM.from_pretrained("flax-community/roberta-base-als") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
This project pretrains a roberta-base on the Alemannic (als) data subset of the OSCAR corpus in JAX/Flax.
We will be using the masked-language modeling loss for pretraining.
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