Instructions to use Veol-CZ/czech-semantic-embeddings with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Veol-CZ/czech-semantic-embeddings with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Veol-CZ/czech-semantic-embeddings", filename="Seznam__dist-mpnet-czeng-cs-en.f16.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Veol-CZ/czech-semantic-embeddings with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Veol-CZ/czech-semantic-embeddings:F16 # Run inference directly in the terminal: llama-cli -hf Veol-CZ/czech-semantic-embeddings:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Veol-CZ/czech-semantic-embeddings:F16 # Run inference directly in the terminal: llama-cli -hf Veol-CZ/czech-semantic-embeddings:F16
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 Veol-CZ/czech-semantic-embeddings:F16 # Run inference directly in the terminal: ./llama-cli -hf Veol-CZ/czech-semantic-embeddings:F16
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 Veol-CZ/czech-semantic-embeddings:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf Veol-CZ/czech-semantic-embeddings:F16
Use Docker
docker model run hf.co/Veol-CZ/czech-semantic-embeddings:F16
- LM Studio
- Jan
- Ollama
How to use Veol-CZ/czech-semantic-embeddings with Ollama:
ollama run hf.co/Veol-CZ/czech-semantic-embeddings:F16
- Unsloth Studio
How to use Veol-CZ/czech-semantic-embeddings with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Veol-CZ/czech-semantic-embeddings to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Veol-CZ/czech-semantic-embeddings to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Veol-CZ/czech-semantic-embeddings to start chatting
- Atomic Chat new
- Docker Model Runner
How to use Veol-CZ/czech-semantic-embeddings with Docker Model Runner:
docker model run hf.co/Veol-CZ/czech-semantic-embeddings:F16
- Lemonade
How to use Veol-CZ/czech-semantic-embeddings with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Veol-CZ/czech-semantic-embeddings:F16
Run and chat with the model
lemonade run user.czech-semantic-embeddings-F16
List all available models
lemonade list
Czech Semantic Embeddings (GGUF, Non-Commercial)
GGUF conversions of Czech semantic embedding models from Seznam with non-commercial license terms.
Included Models
Seznam__dist-mpnet-czeng-cs-en.f16.ggufSeznam__dist-mpnet-czeng-cs-en.q8_0.ggufSeznam__simcse-dist-mpnet-czeng-cs-en.f16.ggufSeznam__simcse-dist-mpnet-czeng-cs-en.q8_0.gguf
Upstream Sources
- https://github.com/seznam/czech-semantic-embedding-models
- https://huggingface.co/Seznam/dist-mpnet-czeng-cs-en
- https://huggingface.co/Seznam/simcse-dist-mpnet-czeng-cs-en
Citation
If you use this model, please cite the original Seznam paper:
- Bednar et al., 2024, Some Like It Small: Czech Semantic Embedding Models for Industry Applications
- https://arxiv.org/abs/2311.13921
@inproceedings{bednavr2024some,
title={Some Like It Small: Czech Semantic Embedding Models for Industry Applications},
author={Bedn{\'a}{\v{r}}, Ji{\v{r}}{\'\i} and N{\'a}plava, Jakub and Baran{\v{c}}{\'\i}kov{\'a}, Petra and Lisick{\`y}, Ond{\v{r}}ej},
booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
volume={38},
number={21},
pages={22734--22742},
year={2024}
}
Usage (llama.cpp)
llama-server -m Seznam__dist-mpnet-czeng-cs-en.q8_0.gguf --embedding --pooling cls
File Integrity
SHA256 checksums are in checksums.txt.
License
This package contains converted checkpoints from upstream models. Respect original model license and terms:
dist-mpnet-czeng-cs-en: CC-BY-NC-SA-4.0simcse-dist-mpnet-czeng-cs-en: CC-BY-NC-SA-4.0
Non-commercial use only. Attribution to Seznam and original model card is required.
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