Instructions to use nyu-mll/roberta-base-100M-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nyu-mll/roberta-base-100M-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nyu-mll/roberta-base-100M-1")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nyu-mll/roberta-base-100M-1") model = AutoModelForMaskedLM.from_pretrained("nyu-mll/roberta-base-100M-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0efdf4a548dc0a6abd5bb560a463fec247ea552022233eb5745d89dee0f79ce3
- Size of remote file:
- 501 MB
- SHA256:
- bd688a226736c445c9086541921c41c68594f8ecd8988707d3ecc57887daef98
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