Sentence Similarity
sentence-transformers
Safetensors
English
qwen3
feature-extraction
skill-retrieval
embedding
Eval Results (legacy)
text-embeddings-inference
Instructions to use anonymous-ed-benchmark/SKILLRET-Embedding-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use anonymous-ed-benchmark/SKILLRET-Embedding-8B with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("anonymous-ed-benchmark/SKILLRET-Embedding-8B") 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:
- 649a07d8a0eb60b113d824b0b08cf6501a6f6a32740542f2282b042ceb5cd7bc
- Size of remote file:
- 11.4 MB
- SHA256:
- b25356ee9ffd2758a5203802eaeaa61b70fce8a0893b890849cf51e0f25f9797
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