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 requirements.txt from tebebe/laya-devops-mlx: direct link, hf CLI and curl.
- Browser
- Download file 191 Bytes
-
https://huggingface.co/tebebe/laya-devops-mlx/resolve/main/requirements.txt
- Command line
-
hf download hf://tebebe/laya-devops-mlx/requirements.txt
-
curl -L -o requirements.txt https://huggingface.co/tebebe/laya-devops-mlx/resolve/main/requirements.txt
191 Bytes
| laya-mlx==0.2.0 | |
| mlx==0.32.2 | |
| tokenizers==0.23.2 | |
| numpy>=1.26,<3 | |
| huggingface-hub>=1.0,<2 | |
| layastudio @ git+https://github.com/biplovgautam/LayaStudio.git@71f1a01466e247c4ac9a8afe681e3491cb0f2e06 | |