Image Classification
Transformers
Safetensors
nula
computer-vision
cnn
cifar10
adversarial-robustness
stress-test
downsampling
anti-aliasing
custom_code
Instructions to use MamaPearl/nula-cifar10-robust-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MamaPearl/nula-cifar10-robust-v0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="MamaPearl/nula-cifar10-robust-v0", trust_remote_code=True) pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModelForImageClassification model = AutoModelForImageClassification.from_pretrained("MamaPearl/nula-cifar10-robust-v0", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "NulaForImageClassification" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_nula.NulaConfig", | |
| "AutoModelForImageClassification": "modeling_nula.NulaForImageClassification" | |
| }, | |
| "model_type": "nula", | |
| "block_channels": [ | |
| 128, | |
| 256, | |
| 512 | |
| ], | |
| "classifier_hidden_dim": 512, | |
| "dtype": "float32", | |
| "id2label": { | |
| "0": "airplane", | |
| "1": "automobile", | |
| "2": "bird", | |
| "3": "cat", | |
| "4": "deer", | |
| "5": "dog", | |
| "6": "frog", | |
| "7": "horse", | |
| "8": "ship", | |
| "9": "truck" | |
| }, | |
| "in_channels": 3, | |
| "input_size": [ | |
| 3, | |
| 32, | |
| 32 | |
| ], | |
| "label2id": { | |
| "airplane": 0, | |
| "automobile": 1, | |
| "bird": 2, | |
| "cat": 3, | |
| "deer": 4, | |
| "dog": 5, | |
| "frog": 6, | |
| "horse": 7, | |
| "ship": 8, | |
| "truck": 9 | |
| }, | |
| "mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "num_classes": 10, | |
| "se_reduction": 16, | |
| "std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "transformers_version": "5.4.0", | |
| "use_residual": true, | |
| "use_se": true, | |
| "use_spatial_attention": false | |
| } | |