Instructions to use phosseini/atomic-roberta-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use phosseini/atomic-roberta-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="phosseini/atomic-roberta-large")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("phosseini/atomic-roberta-large") model = AutoModelForMaskedLM.from_pretrained("phosseini/atomic-roberta-large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 47e9862e1f4065501567a1e9380f95a416dfee32c5da25170d829c99b6595097
- Size of remote file:
- 1.42 GB
- SHA256:
- 37368edb109b7e8a59c4e71b56a27d5a3024ac93c9eb1f4d52d15641ee27d753
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