Model2Vec
Safetensors
sentence-transformers
multilingual
English
Serbian
embeddings
static-embeddings
Instructions to use Stopwolf/embedic-m2v-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Model2Vec
How to use Stopwolf/embedic-m2v-large with Model2Vec:
from model2vec import StaticModel model = StaticModel.from_pretrained("Stopwolf/embedic-m2v-large") - sentence-transformers
How to use Stopwolf/embedic-m2v-large with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Stopwolf/embedic-m2v-large") 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
| [ | |
| { | |
| "idx": 0, | |
| "name": "0", | |
| "path": ".", | |
| "type": "sentence_transformers.models.StaticEmbedding" | |
| }, | |
| { | |
| "idx": 1, | |
| "name": "1", | |
| "path": "1_Normalize", | |
| "type": "sentence_transformers.models.Normalize" | |
| } | |
| ] |