Text Classification
setfit
Safetensors
sentence-transformers
English
mpnet
generated_from_setfit_trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use carlesoctav/SentimentClassifierDune64shot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use carlesoctav/SentimentClassifierDune64shot with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("carlesoctav/SentimentClassifierDune64shot") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - sentence-transformers
How to use carlesoctav/SentimentClassifierDune64shot with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("carlesoctav/SentimentClassifierDune64shot") 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
Download model_head.pkl from carlesoctav/SentimentClassifierDune64shot: direct link, hf CLI and curl.
- Browser
- Download file 7 kB
-
https://huggingface.co/carlesoctav/SentimentClassifierDune64shot/resolve/main/model_head.pkl
- Command line
-
hf download hf://carlesoctav/SentimentClassifierDune64shot/model_head.pkl
-
curl -L -o model_head.pkl https://huggingface.co/carlesoctav/SentimentClassifierDune64shot/resolve/main/model_head.pkl
7 kB
- Xet hash:
- 5a598b80bb714b69e50f3666a8f0f32240db894d753b28e91520ede0f2bb022e
- Size of remote file:
- 7 kB
- SHA256:
- 1d47ad04c5caf47e03c41efcd026345e1455e6170d4dfeef5b712ba1cabb0287
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