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jina-embeddings-v5-text-small-text-matching
by jinaai · source Hugging Face · updated 2026-04-15
cc-by-nc-4.0378 MB~1 GB RAMsource aliveunlabeled
jina-embeddings-v5-text-small-text-matching: Text-Matching-Targeted Embedding Distillation
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Source and license
- Source: https://huggingface.co/jinaai/jina-embeddings-v5-text-small-text-matching
- License: cc-by-nc-4.0 (restricted license: terms at the source apply)
- Requirements: about 1 GB of RAM, 378 MB on disk (estimate: suggested file size × 1.15 + 0.5 GB; a real measurement comes with lsh models). Runs with llama.cpp.
- Tags:
llama.cpponnxsafetensorsggufqwen3embeddingllama-cppjina-embeddings-v5feature-extractionmtebvllmsentence-transformerssentence-similaritymultilingualtext-embeddings-inferenceconversational
Numbers
- 116,726 downloads on Hugging Face
- 13 likes
- license cc-by-nc-4.0
- 0.4 GB for v5-small-text-matching-Q4_K_M.gguf
- 327,838 npm downloads a week for node-llama-cpp
- latest node-llama-cpp@3.22.1
Numbers as of 2026-10-02 21:00 UTC, from the source API.
Summary
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Files
| file | quant | size |
|---|---|---|
model.safetensors | 1.1 GB | |
onnx/model.onnx | 1 MB | |
v5-small-text-matching-F16.gguf | F16 | 1.1 GB |
v5-small-text-matching-IQ1_M.gguf | IQ1_M | 206 MB |
v5-small-text-matching-IQ1_S.gguf | IQ1_S | 198 MB |
v5-small-text-matching-IQ2_M.gguf | IQ2_M | 253 MB |
v5-small-text-matching-IQ2_XXS.gguf | IQ2_XXS | 219 MB |
v5-small-text-matching-IQ4_NL.gguf | IQ4_NL | 364 MB |
v5-small-text-matching-IQ4_XS.gguf | IQ4_XS | 351 MB |
v5-small-text-matching-Q2_K.gguf | Q2_K | 283 MB |
v5-small-text-matching-Q3_K_M.gguf | Q3_K_M | 331 MB |
v5-small-text-matching-Q4_K_M.gguf | Q4_K_M | 378 MB |
v5-small-text-matching-Q5_K_M.gguf | Q5_K_M | 424 MB |
v5-small-text-matching-Q5_K_S.gguf | Q5_K_S | 416 MB |
v5-small-text-matching-Q6_K.gguf | Q6_K | 472 MB |
v5-small-text-matching-Q8_0.gguf | Q8_0 | 610 MB |
From the source README
jina-embeddings-v5-text-small-text-matching: Text-Matching-Targeted Embedding Distillation
Elastic Inference Service | ArXiv | Release Note | Blog
Model Overview
`jina-embeddings-v5-text-small-text-matching` is a compact, high-performance text embedding model designed for text-matching.
It is part of the jina-embeddings-v5-text model family, which also includes jina-embeddings-v5-text-nano, a smaller model for more resource-constrained use cases.
Trained using a novel approach that combines distillation with task-specific contrastive losses, `jina-embeddings-v5-text-small-text-matching` outperforms existing state-of-the-art models of similar size across diverse embedding benchmarks.
| Feature | Value |
| --- | --- |
| Parameters | 677M |
| Supported Tasks | `text-matching`|
| Max Sequence Length | 32768 |
| Embedding Dimension | 1024 |
| Matryoshka Dimensions | 32, 64, 128, 256, 512, 768, 1024 |
| Pooling Strategy | Last-token pooling |
| Base Model | jinaai/jina-embeddings-v5-text-small |
Training and Evaluation
For training details and evaluation results, see our technical report.
Usage
Requirements
The following Python packages are required:
- `transformers>=5.1.0`
- `torch>=2.8.0`
- `peft>=0.15.2`
- `vllm>=0.15.1`
Card id model:hf:jinaai/jina-embeddings-v5-text-small-text-matching · collected 2026-10-02 21:00 UTC · JSON