Instructions to use flax-community/roberta-base-als-demo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flax-community/roberta-base-als-demo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="flax-community/roberta-base-als-demo")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("flax-community/roberta-base-als-demo") model = AutoModelForMaskedLM.from_pretrained("flax-community/roberta-base-als-demo") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9b8769998fc6864913b53c1903e9e60914883be8801cb492c2579dff2aa70e53
- Size of remote file:
- 499 MB
- SHA256:
- 6d2146f8f76daab4cd4d473f9a3b61dba2531a6e5eccf44f77f562369a9cc31f
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