Instructions to use nyu-mll/roberta-base-1B-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nyu-mll/roberta-base-1B-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nyu-mll/roberta-base-1B-1")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nyu-mll/roberta-base-1B-1") model = AutoModelForMaskedLM.from_pretrained("nyu-mll/roberta-base-1B-1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f7ac3375c53d828f51f53565ee34c22c81337e9ada6b3d6bef6b1b88eda7faaf
- Size of remote file:
- 499 MB
- SHA256:
- 8ec29a047dce736dadcc0a3c3d5973f665f2cdf86cfd78825006edffbcef7bdf
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.