Instructions to use mnmly/utonia-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mnmly/utonia-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir utonia-mlx mnmly/utonia-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
File size: 758 Bytes
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"in_channels": 9,
"order": [
"z",
"z-trans",
"hilbert",
"hilbert-trans"
],
"stride": [
2,
2,
2,
2
],
"enc_depths": [
3,
3,
3,
12,
3
],
"enc_channels": [
54,
108,
216,
432,
576
],
"enc_num_head": [
3,
6,
12,
24,
32
],
"enc_patch_size": [
1024,
1024,
1024,
1024,
1024
],
"mlp_ratio": 4,
"qkv_bias": true,
"qk_scale": null,
"attn_drop": 0.0,
"proj_drop": 0.0,
"drop_path": 0.3,
"shuffle_orders": true,
"pre_norm": true,
"enable_rpe": false,
"enable_flash": true,
"upcast_attention": false,
"upcast_softmax": false,
"traceable": true,
"enc_mode": true,
"mask_token": true,
"rope_base": 10
} |