Text Classification
sentence-transformers
Joblib
Scikit-learn
English
intent-classification
emotion-detection
mental-health
lstm
Instructions to use mindpadi/hybrid_classifier_suite with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use mindpadi/hybrid_classifier_suite with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mindpadi/hybrid_classifier_suite") 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] - Scikit-learn
How to use mindpadi/hybrid_classifier_suite with Scikit-learn:
from huggingface_hub import hf_hub_download import joblib model = joblib.load( hf_hub_download("mindpadi/hybrid_classifier_suite", "sklearn_model.joblib") ) # only load pickle files from sources you trust # read more about it here https://skops.readthedocs.io/en/stable/persistence.html - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f588a913bf0ae32793001c5757e3be53392f6243c8f7fec15ee9ec9e4187e4e4
- Size of remote file:
- 424 Bytes
- SHA256:
- eac48cb4b2c05c457c2d588263b42bd6a4a0f9f6dda738139a963a3fe471db93
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