Sentence Similarity
sentence-transformers
Safetensors
qwen3
feature-extraction
dense
text-embeddings-inference
Instructions to use dwulff/Qwen3-Embedding-0.6B-RLMap with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use dwulff/Qwen3-Embedding-0.6B-RLMap with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("dwulff/Qwen3-Embedding-0.6B-RLMap") 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] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e126971f70bf42814219df1aa457c7cb4eedb1abbc82e285741c1c4086110d38
- Size of remote file:
- 11.4 MB
- SHA256:
- c87c38db060bafb0122019c0c749ec1eb1ae510dae43c93f0042ec51099942e8
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