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", device_map="auto")# 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:
- 0700b5d66c55f8715edaabb702b6b656441798ea9ab26a473bad8895af4ca564
- Size of remote file:
- 334 MB
- SHA256:
- 2f8ca7b942b01c1f0f063e8c21ec7b19726edb85bc2caf6b363de2034ef2471b
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