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Efficient retrieval

# Efficient retrieval

Qwen3 Embedding 0.6B Onnx Uint8
Apache-2.0
This is a quantized model based on ONNX, which is the uint8 quantized version of Qwen/Qwen3-Embedding-0.6B. It reduces the model size while maintaining retrieval performance.
Text Embedding
Q
electroglyph
112
8
Mass Academy Faq Embedder I1 GGUF
This model is a quantized version of ntproctor/mass-academy-faq-embedder, offering multiple quantization type options, suitable for efficient feature extraction and sentence similarity calculation.
Text Embedding Transformers English
M
mradermacher
452
1
Qwen3 Embedding 4B W4A16 G128
Apache-2.0
This is the Qwen3-Embedding-4B model after GPTQ quantization, with significantly reduced video memory usage and minimal performance loss.
Text Embedding
Q
boboliu
141
1
Bge Micro V2
bge_micro is a sentence embedding model based on sentence-transformers, focusing on sentence similarity calculation and feature extraction tasks.
Text Embedding Transformers
B
SmartComponents
468
2
Vectorizer V1 S Multilingual
A multilingual vectorizer developed by Sinequa that generates embedding vectors for input paragraphs or queries, used for similarity calculation and information retrieval.
Text Embedding Transformers Supports Multiple Languages
V
sinequa
322
0
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