Text Classification
setfit
Safetensors
sentence-transformers
English
mpnet
generated_from_setfit_trainer
text-embeddings-inference
Instructions to use carlesoctav/SentimentClassifierDune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use carlesoctav/SentimentClassifierDune with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("carlesoctav/SentimentClassifierDune") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - sentence-transformers
How to use carlesoctav/SentimentClassifierDune with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("carlesoctav/SentimentClassifierDune") 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/SentimentClassifierDune: direct link, hf CLI and curl.
- Browser
- Download file 7.64 kB
-
https://huggingface.co/carlesoctav/SentimentClassifierDune/resolve/main/model_head.pkl
- Command line
-
hf download hf://carlesoctav/SentimentClassifierDune/model_head.pkl
-
curl -L -o model_head.pkl https://huggingface.co/carlesoctav/SentimentClassifierDune/resolve/main/model_head.pkl
7.64 kB
- Xet hash:
- fd7a0738eb01c427938b1482faaa168a5c8c54162a76b76a5efdaf00f04d8fa1
- Size of remote file:
- 7.64 kB
- SHA256:
- 034f8755f06e904c8b226849b7d18e3df523dfbfd93710233551dc41e600eaeb
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