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", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NbAiLab/roberta_des_512") model = AutoModelForMaskedLM.from_pretrained("NbAiLab/roberta_des_512", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 924f7dc66f4a3c7c8ed7e00cf077f8dc436953600c8b553bf522bc1b0ec6d2f9
- Size of remote file:
- 499 MB
- SHA256:
- 6b3ba1f6b07a745bb7e62bf194c7a33cffae28368c55cc6bcfa670ef2ef1e786
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