Instructions to use eeahugs/query-intent-setfit-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- setfit
How to use eeahugs/query-intent-setfit-v1 with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("eeahugs/query-intent-setfit-v1") preds = model.predict(["i loved the spiderman movie!", "pineapple on pizza is the worst"]) print(preds) - sentence-transformers
How to use eeahugs/query-intent-setfit-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("eeahugs/query-intent-setfit-v1") 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 2_Normalize/config.json from eeahugs/query-intent-setfit-v1: direct link, hf CLI and curl.
- Browser
- Download file 97 Bytes
-
https://huggingface.co/eeahugs/query-intent-setfit-v1/resolve/main/2_Normalize/config.json
- Command line
-
hf download hf://eeahugs/query-intent-setfit-v1/2_Normalize/config.json
-
curl -L -o config.json https://huggingface.co/eeahugs/query-intent-setfit-v1/resolve/main/2_Normalize/config.json
97 Bytes
| { | |
| "module_input_name": "sentence_embedding", | |
| "module_output_name": "sentence_embedding" | |
| } |