Instructions to use minishlab/M2V_multilingual_output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Model2Vec
How to use minishlab/M2V_multilingual_output with Model2Vec:
from model2vec import StaticModel model = StaticModel.from_pretrained("minishlab/M2V_multilingual_output") - sentence-transformers
How to use minishlab/M2V_multilingual_output with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("minishlab/M2V_multilingual_output") 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
| { | |
| "cls_token": "[CLS]", | |
| "sep_token": "[SEP]", | |
| "pad_token": "[PAD]", | |
| "unk_token": "[UNK]", | |
| "mask_token": "[MASK]" | |
| } |