Text Classification
setfit
Safetensors
sentence-transformers
new
generated_from_setfit_trainer
custom_code
text-embeddings-inference
Instructions to use diwank/hn-upvote-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use diwank/hn-upvote-classifier with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("diwank/hn-upvote-classifier") - sentence-transformers
How to use diwank/hn-upvote-classifier with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("diwank/hn-upvote-classifier", trust_remote_code=True) 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:
- 01d687f646cb0a631fc45890498b9d0c52b3301d64fe70219b5fa8c6aaa832ad
- Size of remote file:
- 7.01 kB
- SHA256:
- 6108c704aac635569a2907db35cd68667b6f05b912b996b3cb38387a0dc9c209
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