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:
- 7ef63f47e10755c02add1c1a9d3046876299ab0a68d584d9ed69636d255ab655
- Size of remote file:
- 499 MB
- SHA256:
- ce7e40936e38316a1a1ae6e855969daa4dc4d88fff05c624af3dbe9658d8962f
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