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:
- ea1960f7eb4c52f91d6ee9c5916a20d808418281b932fccf8aec88200647522c
- Size of remote file:
- 334 MB
- SHA256:
- 329e467790c4279bd9fc3898cfcb496f84867f92eaf67b1d400b6702264ed71f
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