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
Download corpus_meta.csv from andreiaalexa/scifact-relevance-classifier: direct link, hf CLI and curl.
- Browser
- Download file 7.85 MB
-
https://huggingface.co/andreiaalexa/scifact-relevance-classifier/resolve/main/corpus_meta.csv
- Command line
-
hf download hf://andreiaalexa/scifact-relevance-classifier/corpus_meta.csv
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curl -L -o corpus_meta.csv https://huggingface.co/andreiaalexa/scifact-relevance-classifier/resolve/main/corpus_meta.csv
7.85 MB
File too large to display, you can check the raw version instead.