Text Classification
setfit
Safetensors
sentence-transformers
bert
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use stephen-solka/feed-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use stephen-solka/feed-classifier with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("stephen-solka/feed-classifier") - sentence-transformers
How to use stephen-solka/feed-classifier with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("stephen-solka/feed-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
- Xet hash:
- d12f6b5620ecead6c69bd3da280caeb7813610db7af8fe654debd2b3bc6c6ee1
- Size of remote file:
- 6.03 kB
- SHA256:
- 0c87c8329c19d3437ee5759dab78f7f15dd8871dc0e2b6b56f7b6b7c603b9642
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