Instructions to use nyu-mll/roberta-base-10M-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nyu-mll/roberta-base-10M-3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nyu-mll/roberta-base-10M-3")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nyu-mll/roberta-base-10M-3") model = AutoModelForMaskedLM.from_pretrained("nyu-mll/roberta-base-10M-3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8224d056719f5f7af55593850814e5e9281b1c770e2d2572cb7e6c3e69b74dd6
- Size of remote file:
- 499 MB
- SHA256:
- 3807f40feb6412abfee12d1735649c55a93732c72333266ea26ef418f202c2a0
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