Instructions to use NbAiLab/roberta_des_512 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/roberta_des_512 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NbAiLab/roberta_des_512")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NbAiLab/roberta_des_512") model = AutoModelForMaskedLM.from_pretrained("NbAiLab/roberta_des_512") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4bc04cccdcaecb7c97f98841b21e875dbb1018df2f7c9ee89969a945be95f36f
- Size of remote file:
- 499 MB
- SHA256:
- e32a15f40749179988be2797a96c4eb1bc36534482e3aa64bd79aad207848dd5
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