Instructions to use NbAiLab/roberta_des_512_6e4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/roberta_des_512_6e4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NbAiLab/roberta_des_512_6e4")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NbAiLab/roberta_des_512_6e4") model = AutoModelForMaskedLM.from_pretrained("NbAiLab/roberta_des_512_6e4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 680e78b250637159b4b827db2cf15e7e452bf2af5b9562af1c7778815cdba3e1
- Size of remote file:
- 499 MB
- SHA256:
- c6f3eb9778ab25fdec47cbaedb0f8d7824cd305db3bdac173578ad2206c24161
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.