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 config_sentence_transformers.json from carlesoctav/SentimentClassifierDune: direct link, hf CLI and curl.
- Browser
- Download file 170 Bytes
-
https://huggingface.co/carlesoctav/SentimentClassifierDune/resolve/main/config_sentence_transformers.json
- Command line
-
hf download hf://carlesoctav/SentimentClassifierDune/config_sentence_transformers.json
-
curl -L -o config_sentence_transformers.json https://huggingface.co/carlesoctav/SentimentClassifierDune/resolve/main/config_sentence_transformers.json
170 Bytes
| { | |
| "__version__": { | |
| "sentence_transformers": "2.0.0", | |
| "transformers": "4.7.0", | |
| "pytorch": "1.9.0+cu102" | |
| }, | |
| "prompts": {}, | |
| "default_prompt_name": null | |
| } |