Instructions to use minishlab/potion-multilingual-128m-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Model2Vec
How to use minishlab/potion-multilingual-128m-onnx with Model2Vec:
from model2vec import StaticModel model = StaticModel.from_pretrained("minishlab/potion-multilingual-128m-onnx") - sentence-transformers
How to use minishlab/potion-multilingual-128m-onnx with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("minishlab/potion-multilingual-128m-onnx") 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
- Xet hash:
- e24dadf330af74270e199992227b02ade53628e56659dd69295d4e45f071344c
- Size of remote file:
- 34.6 MB
- SHA256:
- 07db1d0285c879cd514240759f56cb294c5c19f7a79ea5517e56c350ad65df7b
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