Instructions to use ControlNet/marlin_vit_base_ytf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ControlNet/marlin_vit_base_ytf with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ControlNet/marlin_vit_base_ytf", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ControlNet/marlin_vit_base_ytf", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 657 Bytes
91ef1ad | 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 | {
"architectures": [
"MarlinModel"
],
"as_feature_extractor": true,
"attn_drop_rate": 0.0,
"auto_map": {
"AutoConfig": "config.MarlinConfig",
"AutoModel": "marlin.MarlinModel"
},
"decoder_depth": 4,
"decoder_embed_dim": 384,
"decoder_num_heads": 6,
"drop_rate": 0.0,
"encoder_depth": 12,
"encoder_embed_dim": 768,
"encoder_num_heads": 12,
"img_size": 224,
"init_values": 0.0,
"mlp_ratio": 4.0,
"model_type": "marlin",
"n_frames": 16,
"norm_layer": "LayerNorm",
"patch_size": 16,
"qk_scale": null,
"qkv_bias": true,
"torch_dtype": "float32",
"transformers_version": "4.50.3",
"tubelet_size": 2
}
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