Instructions to use macedonizer/al-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use macedonizer/al-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="macedonizer/al-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("macedonizer/al-roberta-base") model = AutoModelForMaskedLM.from_pretrained("macedonizer/al-roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 75af4e6094e8b4a34910d6290c210669fce2a2b7c0f61a96605c03102b856f78
- Size of remote file:
- 2.48 kB
- SHA256:
- 76e94af147a6058719a8d39d23ce6e7afcbeef5b0a1a9f64a3e42e460c1cfa88
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