Instructions to use tokiers/potion-multilingual-128M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Model2Vec
How to use tokiers/potion-multilingual-128M with Model2Vec:
from model2vec import StaticModel model = StaticModel.from_pretrained("tokiers/potion-multilingual-128M") - sentence-transformers
How to use tokiers/potion-multilingual-128M with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tokiers/potion-multilingual-128M") 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
Regenerate tokenizer.tkz as format v13 (self-contained: added/special tokens stored in-file)
64f25fa verified - Xet hash:
- 4fb6037be86015483c1c91a0a549ee52542b609c250e60114ae814e71da730e1
- Size of remote file:
- 43.2 MB
- SHA256:
- b73dca9d4c9a6937c808435e39cf31c80d5f7455761aa837edf066fafd55bad3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.