Instructions to use relbert/relbert-bert-base-nce-semeval2012 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use relbert/relbert-bert-base-nce-semeval2012 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="relbert/relbert-bert-base-nce-semeval2012")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("relbert/relbert-bert-base-nce-semeval2012") model = AutoModel.from_pretrained("relbert/relbert-bert-base-nce-semeval2012", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 923c7eb5430fd4174c465510437a6d25d0e740eee9d9423e0247afbf1b143afd
- Size of remote file:
- 433 MB
- SHA256:
- 3afe057f1acaf7a7295ac67db98822c4ec9db9048f21b55e5cecf8289c75215a
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