Instructions to use mlx-community/VOSR2-fp32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/VOSR2-fp32 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download mlx-community/VOSR2-fp32 --local-dir VOSR2-fp32
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
File size: 1,881 Bytes
b6271fd | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 | {
"transformer": {
"resolution": 512,
"patch_size": 2,
"mlp_ratio": 4,
"use_qknorm": true,
"use_swiglu": true,
"use_rope": true,
"use_rmsnorm": true,
"wo_shift": false,
"dim": 1536,
"depth": 36,
"num_heads": 24,
"ae_type": "qwen",
"ae_path": "preset/ckpts/Qwen-Image-vae-2d",
"time_dist": [
"lognorm",
0,
1.0
],
"cfg_ratio": 0.1,
"cfg_scale": 1.5,
"dinov2_size": 448,
"enc_type": "dinov2l",
"enc_dim": 1024,
"layer_dinov2b_list": [
17
],
"interp_type": "lin",
"encdim_ratio": 3,
"weak_cond_strength_aelq_list": [
0,
0
],
"cond_strength_aelq_list": [
5,
1
],
"t_start": 0,
"t_end": 1,
"auxiliary_time_cond": false,
"distill_type": "onestep"
},
"vae": {
"_class_name": "AutoencoderKLQwenImage2D",
"_diffusers_version": "0.35.0",
"attn_scales": [],
"base_dim": 96,
"dim_mult": [
1,
2,
4,
4
],
"dropout": 0.0,
"latents_mean": [
-0.7571,
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1.5508,
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0.5517,
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0.2503,
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],
"latents_std": [
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1.4541,
2.3275,
2.6558,
1.2196,
1.7708,
2.6052,
2.0743,
3.2687,
2.1526,
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1.5579,
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],
"non_linearity": "silu",
"num_res_blocks": 2,
"temperal_downsample": [
false,
true,
true
],
"z_dim": 16
},
"dinov2": {
"arch": "vit_large",
"patch_size": 14,
"embed_dim": 1024,
"depth_kept": 18,
"num_heads": 16,
"mlp_ratio": 4,
"layerscale": true,
"qkv_bias": true,
"ln_eps": 1e-06,
"input_size": 448,
"feature_layer": 17,
"pos_embed": "interpolated to 448\u00b2 (offset 0.1, bicubic)"
},
"key_contract": "conv (O,kh,kw,I); Sequential children \u2192 layers.N; VAE gamma (C); DINOv2 blocks 0..17 only"
} |