Instructions to use nyu-mll/roberta-base-10M-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nyu-mll/roberta-base-10M-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nyu-mll/roberta-base-10M-1")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nyu-mll/roberta-base-10M-1") model = AutoModelForMaskedLM.from_pretrained("nyu-mll/roberta-base-10M-1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 03b430a16bbe9c74c9abde47113237ee6da936e25f315b3d131dfacbb8c73db0
- Size of remote file:
- 499 MB
- SHA256:
- 7181ec5730b6feea36318b68faf60e776bf79db440ccf0f142c79259e8766b72
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