Instructions to use bigshanedogg/Concerto-Base-SigLIP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bigshanedogg/Concerto-Base-SigLIP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="bigshanedogg/Concerto-Base-SigLIP", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("bigshanedogg/Concerto-Base-SigLIP", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,017 Bytes
081b306 | 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 | {
"auto_map": {
"AutoProcessor": "processing_concerto.ConcertoProcessor"
},
"feature_extractor": {
"auto_map": {
"AutoFeatureExtractor": "feature_extraction_concerto.ConcertoFeatureExtractor",
"AutoProcessor": "processing_concerto.ConcertoProcessor"
},
"feature_extractor_type": "ConcertoFeatureExtractor",
"transform": [
{
"apply_z": true,
"type": "CenterShift"
},
{
"grid_size": 0.02,
"hash_type": "fnv",
"mode": "train",
"return_grid_coord": true,
"return_inverse": true,
"type": "GridSample"
},
{
"type": "NormalizeColor"
},
{
"type": "ToTensor"
},
{
"feat_keys": [
"coord",
"color",
"normal"
],
"keys": [
"coord",
"grid_coord",
"color",
"inverse"
],
"type": "Collect"
}
]
},
"processor_class": "ConcertoProcessor"
}
|