Instructions to use argilla/alpaca-garbage-collector-multilingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use argilla/alpaca-garbage-collector-multilingual with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("argilla/alpaca-garbage-collector-multilingual") 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 argilla/alpaca-garbage-collector-multilingual with setfit:
from setfit import SetFitModel model = SetFitModel.from_pretrained("argilla/alpaca-garbage-collector-multilingual") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8b03b9e079abc849bdd27d0942fa6a77f9e7836db188512be97e4b3d52f415a8
- Size of remote file:
- 5.07 MB
- SHA256:
- cfc8146abe2a0488e9e2a0c56de7952f7c11ab059eca145a0a727afce0db2865
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.