Text Classification
setfit
Safetensors
sentence-transformers
mpnet
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use rovargasc/Classifier_sentiments_IA25-2V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use rovargasc/Classifier_sentiments_IA25-2V2 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("rovargasc/Classifier_sentiments_IA25-2V2") - sentence-transformers
How to use rovargasc/Classifier_sentiments_IA25-2V2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("rovargasc/Classifier_sentiments_IA25-2V2") 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:
- 26b1f9090d02a702d0e6c9ef8a3cb46ef752ec695cc0b835678ebe3f7db47496
- Size of remote file:
- 438 MB
- SHA256:
- cd30188137819ab1d57856bef1886254fe747940e95b04f754e000240b465bc8
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