Instructions to use millat/laya-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use millat/laya-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download millat/laya-mlx --local-dir laya-mlx
- Laya
How to use millat/laya-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: 698 Bytes
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Copyright 2026 laya-mlx contributors
This product includes software derived from Laya:
https://github.com/NandhaKishorM/laya
Copyright Convai Innovations and Laya contributors. Licensed under Apache-2.0.
Upstream source revision: 6a5819129eb220570792e417e49723d697efd76f
The token sequence construction, question rendering, confidence calculation,
presets, email utilities and language router are adapted from Laya.
The neural network is reimplemented using Apple's MLX, following Laya's
DecisionModel and the ModernBERT architecture in Hugging Face Transformers.
Model weights are downloaded separately from Convai Innovations on Hugging Face;
they are not included in this repository.
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