Instructions to use farzadab/testing-model-upload with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use farzadab/testing-model-upload with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="farzadab/testing-model-upload", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("farzadab/testing-model-upload", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 478 Bytes
4b8b024 124e049 4b8b024 124e049 4b8b024 | 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 | {
"architectures": [
"ResinModel"
],
"auto_map": {
"AutoConfig": "configuration_resnet.ResinConfig",
"AutoModel": "modeling_resnet.ResinModel"
},
"avg_down": false,
"base_width": 64,
"block_type": "bottleneck",
"cardinality": 1,
"input_channels": 3,
"layers": [
3,
4,
6,
3
],
"model_type": "resin",
"num_classes": 1000,
"stem_type": "",
"stem_width": 64,
"torch_dtype": "float32",
"transformers_version": "4.41.2"
}
|