MLX
Safetensors
qwen3_5_moe
oq
quantized
benchmark
performance
Mixture of Experts
code
agentic-coding
2-bit
Instructions to use mlx-works/KAT-Coder-V2.5-Dev-oQ2e with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-works/KAT-Coder-V2.5-Dev-oQ2e with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir KAT-Coder-V2.5-Dev-oQ2e mlx-works/KAT-Coder-V2.5-Dev-oQ2e
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
File size: 390 Bytes
74ea377 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | {
"size": {
"longest_edge": 16777216,
"shortest_edge": 65536
},
"patch_size": 16,
"temporal_patch_size": 2,
"merge_size": 2,
"image_mean": [
0.5,
0.5,
0.5
],
"image_std": [
0.5,
0.5,
0.5
],
"processor_class": "Qwen3VLProcessor",
"image_processor_type": "Qwen2VLImageProcessorFast"
} |