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
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