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
File size: 4,779 Bytes
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"release": "Laya DevOps v29 early preview",
"checkpoint": "devops-v29-p08-r1",
"created_utc": "2026-10-20T13:00:52.266776+00:00",
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"revision": "f2b4faf51023039425946074e2cf1361d2db11d5"
},
"encoder": "jhu-clsp/mmBERT-base",
"teacher_assistance": [
"Sol",
"Astra"
],
"teacher_role": "Synthetic data authoring, scenario design and development assistance; these are not checkpoint weight ancestors. Exact per-row teacher attribution was not independently recorded.",
"effective_chunks": [
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}
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