Feature Extraction
sentence-transformers
Safetensors
English
bert
sentence-similarity
agents
rag
embeddings
llmops
text-embeddings-inference
Instructions to use hharsha/agentic-systems-minilm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use hharsha/agentic-systems-minilm with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("hharsha/agentic-systems-minilm") sentences = [ "hybrid search and reranking for RAG", "RetrievalLab shows advanced RAG with hybrid search and cross-encoder reranking.", "A cooking recipe for pasta carbonara.", "AgentFleet runs multi-agent task DAGs with cost governance." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
File size: 241 Bytes
906f4fa | 1 2 3 4 5 6 7 8 9 10 | {
"transformer_task": "feature-extraction",
"modality_config": {
"text": {
"method": "forward",
"method_output_name": "last_hidden_state"
}
},
"module_output_name": "token_embeddings"
} |