Text Classification
Scikit-learn
sentence-transformers
English
information-retrieval
claim-verification
scifact
evidence-relevance
Eval Results (legacy)
Instructions to use andreiaalexa/scifact-relevance-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Scikit-learn
How to use andreiaalexa/scifact-relevance-classifier with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("andreiaalexa/scifact-relevance-classifier", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - sentence-transformers
How to use andreiaalexa/scifact-relevance-classifier with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("andreiaalexa/scifact-relevance-classifier") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
upload corpus_embeddings.npy
Browse files- corpus_embeddings.npy +3 -0
corpus_embeddings.npy
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version https://git-lfs.github.com/spec/v1
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oid sha256:4094ce196ce78ed67962f8690fe3e54cfb69d3cf920d501b6b55cd8eaba8834d
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size 7961216
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