How to use DataForGood/balance-tes-haters-classifier with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("DataForGood/balance-tes-haters-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]
How to use DataForGood/balance-tes-haters-classifier with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("DataForGood/balance-tes-haters-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
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