Instructions to use macedonizer/gr-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use macedonizer/gr-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="macedonizer/gr-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("macedonizer/gr-roberta-base") model = AutoModelForMaskedLM.from_pretrained("macedonizer/gr-roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0e0d87c6b7a5dddbc4c43c08a7a8dae2d134bf125e464e12d46c2776e4b2990b
- Size of remote file:
- 2.48 kB
- SHA256:
- 1da6591f3163a42e39ec6f37cf206a1e4f7c3565047d7d28972adc7542d0322e
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