Sentence Similarity
sentence-transformers
RKLLM
English
Chinese
rk3588
rockchip
npu
quantized
qwen3
embedding
Instructions to use GatekeeperZA/Qwen3-Embedding-0.6B-RKLLM-v1.2.3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use GatekeeperZA/Qwen3-Embedding-0.6B-RKLLM-v1.2.3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("GatekeeperZA/Qwen3-Embedding-0.6B-RKLLM-v1.2.3") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - RKLLM
How to use GatekeeperZA/Qwen3-Embedding-0.6B-RKLLM-v1.2.3 with RKLLM:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
| license: apache-2.0 | |
| base_model: Qwen/Qwen3-Embedding-0.6B | |
| tags: | |
| - rkllm | |
| - rk3588 | |
| - rockchip | |
| - npu | |
| - quantized | |
| - qwen3 | |
| - embedding | |
| - sentence-transformers | |
| language: | |
| - en | |
| - zh | |
| pipeline_tag: sentence-similarity | |
| # Qwen3-Embedding-0.6B — RKLLM v1.2.3 (w8a8, RK3588) | |
| RKLLM conversion of [Qwen/Qwen3-Embedding-0.6B](https://huggingface.co/Qwen/Qwen3-Embedding-0.6B) for Rockchip RK3588 NPU inference. | |
| Converted with RKLLM Toolkit v1.2.3. This model generates dense vector embeddings for semantic search, RAG pipelines, and similarity tasks — all running on the NPU without a GPU. | |
| ## Key Details | |
| | Property | Value | | |
| |----------|-------| | |
| | Base Model | Qwen/Qwen3-Embedding-0.6B | | |
| | Toolkit Version | RKLLM Toolkit v1.2.3 | | |
| | Runtime Version | RKLLM Runtime ≥ v1.2.1 (v1.2.3 recommended) | | |
| | Quantization | w8a8 (8-bit weights, 8-bit activations) | | |
| | Target Platform | RK3588 | | |
| | NPU Cores | 3 | | |
| | Optimization Level | 1 | | |
| | Hybrid Ratio | 0.5 | | |
| | Model Type | Embedding | | |
| | Languages | English, Chinese (multilingual) | | |
| ## Why This Model? | |
| Running a dedicated embedding model on the RK3588 NPU allows the main LLM to use the full NPU without context-switching. Qwen3-Embedding-0.6B achieves strong retrieval performance at a compact size, making it ideal for local RAG pipelines on edge hardware. | |
| Pair with the Qwen3-Reranker-0.6B for a complete retrieval stack. | |
| ## Hardware Tested | |
| - **Orange Pi 5 Plus** — RK3588, 16GB RAM, Armbian Linux | |
| - RKNPU driver 0.9.8 | |
| - RKLLM Runtime v1.2.3 | |
| ## Usage | |
| ### With the RKLLM Embedding Service | |
| ```bash | |
| mkdir -p ~/models/Qwen3-Embedding-0.6B | |
| cd ~/models/Qwen3-Embedding-0.6B | |
| git lfs install && git clone https://huggingface.co/GatekeeperZA/Qwen3-Embedding-0.6B-RKLLM-v1.2.3 . | |
| ``` | |
| Use with [GatekeeperZA/RKLLM-API-Server](https://github.com/GatekeeperZA/RKLLM-API-Server) embedding endpoint. | |
| ## File Listing | |
| | File | Description | | |
| |------|-------------| | |
| | `Qwen3-Embedding-0.6B-rk3588-w8a8-opt-1-hybrid-ratio-0.5.rkllm` | Quantized embedding model for RK3588 NPU | | |
| ## Compatibility Notes | |
| - Minimum runtime: RKLLM Runtime v1.2.1. v1.2.3 recommended. | |
| - RKNPU driver: ≥ 0.9.6 | |
| - SoCs: RK3588 / RK3588S. Not compatible with RK3576 without reconversion. | |
| - RAM: ~1GB loaded. | |
| ## Acknowledgements | |
| - Alibaba Qwen Team for Qwen3-Embedding | |
| - Rockchip / airockchip for the RKLLM toolkit and runtime | |
| - Converted by [GatekeeperZA](https://huggingface.co/GatekeeperZA) | |