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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9640c6ff34276cae031555ad1821cd62164bef2666bd0f11651fe6d774dfaed6
- Size of remote file:
- 501 MB
- SHA256:
- 9606de38a8e8e553161b8c1396efb5bd4e778d52123dde45dd253b8cc1192c91
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