Instructions to use iamEvanYT/K2-Horizon-MoVA-36B-A4B-MLX-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use iamEvanYT/K2-Horizon-MoVA-36B-A4B-MLX-4bit with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir K2-Horizon-MoVA-36B-A4B-MLX-4bit iamEvanYT/K2-Horizon-MoVA-36B-A4B-MLX-4bit
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
| library_name: mlx | |
| license: apache-2.0 | |
| base_model: IFM/K2-Horizon-MoVA-36B-A4B | |
| tags: | |
| - mlx | |
| - apple-silicon | |
| - mixture-of-experts | |
| # K2-Horizon-MoVA-36B-A4B-MLX-4bit | |
| 4-bit affine (group size 64) MLX conversion of | |
| [IFM/K2-Horizon-MoVA-36B-A4B](https://huggingface.co/IFM/K2-Horizon-MoVA-36B-A4B) | |
| for Apple Silicon via `mlx-lm`. | |
| The K2 MoVA architecture has no stock `mlx-lm` implementation, so this repo | |
| ships a custom `k2_horizon.py`, referenced from `config.json` (`model_file`). | |
| MoE/MoVA router matrices are kept in BF16; all large projections are 4-bit. | |
| Measured on a 64 GB M4 Pro Mac mini: ~43 tok/s single-stream decode, | |
| 18.9 GB peak RSS, perplexity 2.1-8.6 on generic prose/code. | |
| ```python | |
| from mlx_lm import load, stream_generate | |
| model, tokenizer = load("iamEvanYT/K2-Horizon-MoVA-36B-A4B-MLX-4bit") | |
| for chunk in stream_generate(model, tokenizer, "Hello.", max_tokens=64): | |
| print(chunk.text, end="", flush=True) | |
| ``` | |