Instructions to use minishlab/potion-base-8M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Model2Vec
How to use minishlab/potion-base-8M with Model2Vec:
from model2vec import StaticModel model = StaticModel.from_pretrained("minishlab/potion-base-8M") - sentence-transformers
How to use minishlab/potion-base-8M with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("minishlab/potion-base-8M") 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
Multilanguage Rag sentence-transformers alternative
#5
by devops724 - opened
i see this
It is a distilled version of the baai/bge-base-en-v1.5 Sentence Transformer
this mean it can't be used for query over database with multi language content ?
Hi @devops724 , this model is indeed meant for English, but we do have a multilingual model as well: https://huggingface.co/minishlab/M2V_multilingual_output. Alternatively, you can also distill a multilingual model yourself using the Model2Vec library.