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
Upload utonia_config.json with huggingface_hub
Browse files- utonia_config.json +59 -0
utonia_config.json
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{
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"in_channels": 9,
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"order": [
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"z",
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"z-trans",
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"hilbert",
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"hilbert-trans"
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],
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"stride": [
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2,
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2,
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2,
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2
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],
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"enc_depths": [
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3,
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3,
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3,
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12,
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3
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],
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"enc_channels": [
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54,
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108,
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216,
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432,
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576
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],
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"enc_num_head": [
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3,
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6,
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12,
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24,
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32
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],
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"enc_patch_size": [
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1024,
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1024,
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1024,
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1024,
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1024
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],
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"mlp_ratio": 4,
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"qkv_bias": true,
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"qk_scale": null,
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"attn_drop": 0.0,
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"proj_drop": 0.0,
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"drop_path": 0.3,
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"shuffle_orders": true,
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"pre_norm": true,
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"enable_rpe": false,
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"enable_flash": true,
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"upcast_attention": false,
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"upcast_softmax": false,
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"traceable": true,
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"enc_mode": true,
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"mask_token": true,
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"rope_base": 10
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}
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