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
- Xet hash:
- a8521c128be475d550f0697edd6a176ea605d390f9fc369ce02c11ae3451c6dc
- Size of remote file:
- 499 MB
- SHA256:
- 81dadcf31f203347f15683dd2815da9fb3e466d0f761e5356ad7afcabe8515e5
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