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)
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