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")# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from flax-community/roberta-base-als-demo: direct link, hf CLI and curl.
- Browser
- Download file 944 Bytes
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https://huggingface.co/flax-community/roberta-base-als-demo/resolve/main/README.md
- Command line
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hf download hf://flax-community/roberta-base-als-demo/README.md
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curl -L -o README.md https://huggingface.co/flax-community/roberta-base-als-demo/resolve/main/README.md
944 Bytes
roberta-base-als-demo
roberta-base-als-demo is a model trained by Patrick von Platen to demonstrate how to train a roberta-base model from scratch on the Alemannic language.
This is part of the Flax/Jax Community Week, organised by HuggingFace and TPU usage sponsored by Google.