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 model.safetensors from tebebe/laya-devops-mlx: direct link, hf CLI and curl.
- Browser
- Download file 644 MB
-
https://huggingface.co/tebebe/laya-devops-mlx/resolve/main/model.safetensors
- Command line
-
hf download hf://tebebe/laya-devops-mlx/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/tebebe/laya-devops-mlx/resolve/main/model.safetensors
644 MB
- Xet hash:
- e4b95f89579c448b7ab7bae563725fe572e18b2aa4506079a517ab1163951210
- Size of remote file:
- 644 MB
- SHA256:
- 39770ecfc0a5583102c6dccb68beb4fa2f9c3a7781a439aae9b3316c886cd353
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