Instructions to use relbert/relbert-roberta-base-nce-semeval2012-mask with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use relbert/relbert-roberta-base-nce-semeval2012-mask with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="relbert/relbert-roberta-base-nce-semeval2012-mask")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("relbert/relbert-roberta-base-nce-semeval2012-mask") model = AutoModel.from_pretrained("relbert/relbert-roberta-base-nce-semeval2012-mask", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 62d5cfa1d356703c7807683c39cda4557be1c777b65043a6a3dfe6479b899239
- Size of remote file:
- 499 MB
- SHA256:
- b7a7bc346bcc1327a7da0785e8c791e06f1678ab2d3e0920793924906d741718
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