Text Classification
MLX
Safetensors
Laya
Polish
English
devops
decision-model
apple-silicon
experimental
synthetic-data
claude-code
litellm
Instructions to use tebebe/laya-devops-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use tebebe/laya-devops-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download tebebe/laya-devops-mlx --local-dir laya-devops-mlx
- Laya
How to use tebebe/laya-devops-mlx with Laya:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Download serve.sh from tebebe/laya-devops-mlx: direct link, hf CLI and curl.
- Browser
- Download file 197 Bytes
-
https://huggingface.co/tebebe/laya-devops-mlx/resolve/main/serve.sh
- Command line
-
hf download hf://tebebe/laya-devops-mlx/serve.sh
-
curl -L -o serve.sh https://huggingface.co/tebebe/laya-devops-mlx/resolve/main/serve.sh
197 Bytes
| set -eu | |
| release_dir=$(CDPATH= cd -- "$(dirname -- "$0")" && pwd) | |
| release_python=${LAYA_PYTHON:-"$release_dir/.venv/bin/python"} | |
| exec "$release_python" "$release_dir/start_server.py" "$@" | |