Instructions to use dacanizalesconvers/material-surface-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dacanizalesconvers/material-surface-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dacanizalesconvers/material-surface-classifier") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("dacanizalesconvers/material-surface-classifier") model = AutoModelForImageClassification.from_pretrained("dacanizalesconvers/material-surface-classifier") - timm
How to use dacanizalesconvers/material-surface-classifier with timm:
import timm model = timm.create_model("hf_hub:dacanizalesconvers/material-surface-classifier", pretrained=True) - Notebooks
- Google Colab
- Kaggle
| { | |
| "architecture": "mobilenetv3_large_100", | |
| "architectures": [ | |
| "TimmWrapperForImageClassification" | |
| ], | |
| "do_pooling": true, | |
| "dtype": "float32", | |
| "initializer_range": 0.02, | |
| "label_names": [ | |
| "asphalt", | |
| "concrete", | |
| "metal", | |
| "other", | |
| "wood" | |
| ], | |
| "model_args": null, | |
| "model_type": "timm_wrapper", | |
| "num_classes": 5, | |
| "num_features": 1280, | |
| "pretrained_cfg": { | |
| "classifier": "classifier", | |
| "crop_mode": "center", | |
| "crop_pct": 0.875, | |
| "custom_load": false, | |
| "first_conv": "conv_stem", | |
| "fixed_input_size": false, | |
| "input_size": [ | |
| 3, | |
| 224, | |
| 224 | |
| ], | |
| "interpolation": "bicubic", | |
| "mean": [ | |
| 0.485, | |
| 0.456, | |
| 0.406 | |
| ], | |
| "pool_size": [ | |
| 7, | |
| 7 | |
| ], | |
| "std": [ | |
| 0.229, | |
| 0.224, | |
| 0.225 | |
| ], | |
| "tag": "ra_in1k" | |
| }, | |
| "transformers_version": "5.7.0", | |
| "use_cache": false | |
| } | |