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
File size: 338 Bytes
b55b047 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | {
"project": "Scientific evidence relevance classification",
"embedding_model": "intfloat/e5-small-v2",
"field_variant": "title_abstract",
"classifier": "hist_gradient_boosting",
"feature_dim": 1537,
"label2id": {
"not_relevant": 0,
"relevant": 1
},
"id2label": {
"0": "not_relevant",
"1": "relevant"
}
} |