Instructions to use funn/t5-toxicity-ranker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use funn/t5-toxicity-ranker with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("funn/t5-toxicity-ranker") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- df1d85eda9a7d3cbedb7a1c4b60ae4d56daf1c5b332c63c74f1d0d1d39f8d5a6
- Size of remote file:
- 439 MB
- SHA256:
- a1d55f8a48c9a542472184fc780adf2b5c499a7b22f9718ea047035895a72f76
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