Feature Extraction
GGUF
multilingual
llama.cpp
embedding
eurobert
llama-cpp
jina-embeddings-v5
🇪🇺 Region: EU
Instructions to use jinaai/jina-embeddings-v5-text-nano-clustering-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use jinaai/jina-embeddings-v5-text-nano-clustering-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf jinaai/jina-embeddings-v5-text-nano-clustering-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf jinaai/jina-embeddings-v5-text-nano-clustering-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf jinaai/jina-embeddings-v5-text-nano-clustering-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf jinaai/jina-embeddings-v5-text-nano-clustering-GGUF:Q4_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf jinaai/jina-embeddings-v5-text-nano-clustering-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf jinaai/jina-embeddings-v5-text-nano-clustering-GGUF:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf jinaai/jina-embeddings-v5-text-nano-clustering-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf jinaai/jina-embeddings-v5-text-nano-clustering-GGUF:Q4_K_M
Use Docker
docker model run hf.co/jinaai/jina-embeddings-v5-text-nano-clustering-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use jinaai/jina-embeddings-v5-text-nano-clustering-GGUF with Ollama:
ollama run hf.co/jinaai/jina-embeddings-v5-text-nano-clustering-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use jinaai/jina-embeddings-v5-text-nano-clustering-GGUF with Docker Model Runner:
docker model run hf.co/jinaai/jina-embeddings-v5-text-nano-clustering-GGUF:Q4_K_M
- Lemonade
How to use jinaai/jina-embeddings-v5-text-nano-clustering-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull jinaai/jina-embeddings-v5-text-nano-clustering-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.jina-embeddings-v5-text-nano-clustering-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
add Elastic Inference Service usage
Browse files
README.md
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## Usage with llama.cpp
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```bash
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# Build llama.cpp (upstream)
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git clone https://github.com/ggml-org/llama.cpp
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## Usage with llama.cpp
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<details open>
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<summary>via <a href="https://www.elastic.co/docs/explore-analyze/elastic-inference/eis">Elastic Inference Service</a></summary>
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The fastest way to use v5-text in production. Elastic Inference Service (EIS) provides managed embedding inference with built-in scaling, so you can generate embeddings directly within your Elastic deployment.
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```bash
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PUT _inference/text_embedding/jina-v5
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{
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"service": "elastic",
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"service_settings": {
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"model_id": "jina-embeddings-v5-text-nano"
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}
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}
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```
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See the [Elastic Inference Service documentation](https://www.elastic.co/docs/explore-analyze/elastic-inference/eis) for setup details.
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</details>
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```bash
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# Build llama.cpp (upstream)
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git clone https://github.com/ggml-org/llama.cpp
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