sentence-transformers
Safetensors
bert
embeddings
retrieval
northeast-india
low-resource
multilingual
RAG
Instructions to use MWirelabs/ne-embed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use MWirelabs/ne-embed with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("MWirelabs/ne-embed") 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
| { | |
| "transformer_task": "feature-extraction", | |
| "modality_config": { | |
| "text": { | |
| "method": "forward", | |
| "method_output_name": "last_hidden_state" | |
| } | |
| }, | |
| "module_output_name": "token_embeddings" | |
| } |