Instructions to use mrm8488/RoBasquERTa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/RoBasquERTa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mrm8488/RoBasquERTa")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mrm8488/RoBasquERTa") model = AutoModelForMaskedLM.from_pretrained("mrm8488/RoBasquERTa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 920f5dc641c642237fc996a5085661ed0c6b9ddf10fe63ee8cdc3bac600b93e4
- Size of remote file:
- 336 MB
- SHA256:
- 1c43d05622a1da53ae6ca548e1714b5f68c2e52371652880ee2b03a67055b147
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