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 tokenizer/tokenizer.json from tebebe/laya-devops-mlx: direct link, hf CLI and curl.
- Browser
- Download file 37.4 MB
-
https://huggingface.co/tebebe/laya-devops-mlx/resolve/main/tokenizer/tokenizer.json
- Command line
-
hf download hf://tebebe/laya-devops-mlx/tokenizer/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/tebebe/laya-devops-mlx/resolve/main/tokenizer/tokenizer.json
37.4 MB
- Xet hash:
- 685c32d34935176f8bb25709789730f417a9582e34c52b174066d6499741c96a
- Size of remote file:
- 37.4 MB
- SHA256:
- 4cda780d55bb139b64c00fd9c580f6f42a3106d46c5db05190902de66528be22
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