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, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "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" | |
| } | |