Instructions to use SceneWorks/wan2.2-ti2v-5b-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use SceneWorks/wan2.2-ti2v-5b-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir wan2.2-ti2v-5b-mlx SceneWorks/wan2.2-ti2v-5b-mlx
- Wan2.2
How to use SceneWorks/wan2.2-ti2v-5b-mlx with Wan2.2:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
File size: 1,222 Bytes
e2af279 | 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 | {
"boundary": 0.0,
"cross_attn_norm": true,
"dim": 3072,
"dual_model": false,
"eps": 1e-6,
"ffn_dim": 14336,
"frame_num": 81,
"freq_dim": 256,
"in_dim": 48,
"max_area": 901120,
"model_type": "ti2v",
"model_version": "2.2",
"num_heads": 24,
"num_layers": 30,
"num_train_timesteps": 1000,
"out_dim": 48,
"patch_size": [
1,
2,
2
],
"qk_norm": true,
"sample_fps": 24,
"sample_guide_scale": 5.0,
"sample_neg_prompt": "色调艳丽,过曝,静态,细节模糊不清,字幕,风格,作品,画作,画面,静止,整体发灰,最差质量,低质量,JPEG压缩残留,丑陋的,残缺的,多余的手指,画得不好的手部,画得不好的脸部,畸形的,毁容的,形态畸形的肢体,手指融合,静止不动的画面,杂乱的背景,三条腿,背景人很多,倒着走",
"sample_shift": 5.0,
"sample_steps": 40,
"t5_dim": 4096,
"t5_dim_attn": 4096,
"t5_dim_ffn": 10240,
"t5_num_buckets": 32,
"t5_num_heads": 64,
"t5_num_layers": 24,
"t5_vocab_size": 256384,
"text_dim": 4096,
"text_len": 512,
"vae_stride": [
4,
16,
16
],
"vae_z_dim": 48,
"window_size": [
-1,
-1
]
} |