Instructions to use sud977/intents-setfit-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sud977/intents-setfit-model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sud977/intents-setfit-model") 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] - setfit
How to use sud977/intents-setfit-model with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("sud977/intents-setfit-model") - Notebooks
- Google Colab
- Kaggle
/var/folders/lm/k69sycyx5538ldsk5n0ln5000000gn/T/tmp7vmgfud9/killshot977/intents-setfit-model
This is a SetFit model that can be used for text classification. The model has been trained using an efficient few-shot learning technique that involves:
- Fine-tuning a Sentence Transformer with contrastive learning.
- Training a classification head with features from the fine-tuned Sentence Transformer.
Usage
To use this model for inference, first install the SetFit library:
python -m pip install setfit
You can then run inference as follows:
from setfit import SetFitModel
# Download from Hub and run inference
model = SetFitModel.from_pretrained("/var/folders/lm/k69sycyx5538ldsk5n0ln5000000gn/T/tmp7vmgfud9/killshot977/intents-setfit-model")
# Run inference
preds = model(["I want to tour this community","do you have a 1 bedroom", "what is your availability", "can i visit this place?", "you really did me a solid!"])
print(preds)
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