Feature Extraction
sentence-transformers
Safetensors
Chinese
English
minimind
text-embedding
chinese
qwen3-embedding
matryoshka
Mixture of Experts
Instructions to use Muzian/minimind-embedding-moe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Muzian/minimind-embedding-moe with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Muzian/minimind-embedding-moe") 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
File size: 285 Bytes
9ac5b4d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | [
{
"idx": 0,
"name": "0",
"type": "sentence_transformers.models.Transformer"
},
{
"idx": 1,
"name": "1",
"type": "sentence_transformers.models.Pooling",
"args": {
"word_embedding_dimension": 768,
"pooling_mode_lasttoken": true
}
}
] |