sentence-transformers
English
agentweave_semantic_router
agentweave
agentic-ai
tool-routing
semantic-routing
function-calling
cpu
minilm
pre-inference-routing
Instructions to use sauravsingla08/AgentWeave-Router-MiniLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sauravsingla08/AgentWeave-Router-MiniLM with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sauravsingla08/AgentWeave-Router-MiniLM") 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
| { | |
| "model_type": "agentweave_semantic_router", | |
| "architecture": "prototype_cosine_router", | |
| "encoder_model": "sentence-transformers/all-MiniLM-L6-v2", | |
| "encoder_usage": "frozen runtime dependency", | |
| "weights_included": false, | |
| "fine_tuned": false, | |
| "embedding_dimension": 384, | |
| "similarity": "cosine", | |
| "normalize_embeddings": true, | |
| "default_top_k": 3, | |
| "training": "none; prototype-based semantic routing", | |
| "version": "0.1.0" | |
| } | |