Instructions to use KVCHub/KaiLu-2-933M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use KVCHub/KaiLu-2-933M with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("KVCHub/KaiLu-2-933M") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use KVCHub/KaiLu-2-933M with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "KVCHub/KaiLu-2-933M" --prompt "Once upon a time"
- Atomic Chat
KaiLu 2 (933M)
KaiLu 2 is a fast, lightweight language model built from scratch for Apple Silicon (Mac, iPhone, and iPad) using Apple MLX.
It packs 933 million parameters into a tiny 609 MB file that runs completely offline on your device with zero cloud servers and zero subscriptions.
⚡ Highlights
- 100% From Scratch: Trained from random initialization on Apple Silicon Metal GPUs.
- Tiny & Lightweight: Only 609 MB on disk, using just 1.15 GB of RAM.
- Blazing Fast: Streams over 260 tokens per second on Apple Silicon.
- 100% Offline & Private: Everything stays on your local device.
- Downloads last month
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Model size
0.2B params
Tensor type
BF16
·
U32 ·
Hardware compatibility
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