Text Classification
setfit
Safetensors
sentence-transformers
mpnet
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use souvenger/NLP2Linux with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use souvenger/NLP2Linux with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("souvenger/NLP2Linux") - sentence-transformers
How to use souvenger/NLP2Linux with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("souvenger/NLP2Linux") 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:
- a3483bd30a4a0f77021b909012218c95345b9874c42b5cb8874920afe1f8bbcc
- Size of remote file:
- 438 MB
- SHA256:
- b4730a21856796350bb4948458ae4baaa872c1a2720a4565a320053a7c0efc62
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