Image Classification
Transformers
PyTorch
TensorBoard
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use Woleek/bg-classif with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Woleek/bg-classif with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Woleek/bg-classif") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Woleek/bg-classif") model = AutoModelForImageClassification.from_pretrained("Woleek/bg-classif", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from Woleek/bg-classif: direct link, hf CLI and curl.
- Browser
- Download file 1.09 kB
-
https://huggingface.co/Woleek/bg-classif/resolve/104f28624af969b28bbf72594de7d752c8545bf2/config.json
- Command line
-
hf download hf://Woleek/bg-classif@104f28624af969b28bbf72594de7d752c8545bf2/config.json
-
curl -L -o config.json https://huggingface.co/Woleek/bg-classif/resolve/104f28624af969b28bbf72594de7d752c8545bf2/config.json
1.09 kB
| { | |
| "_name_or_path": "google/vit-base-patch16-224", | |
| "architectures": [ | |
| "ViTForImageClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.0, | |
| "encoder_stride": 16, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.0, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "airport", | |
| "1": "bathroom", | |
| "10": "zoo", | |
| "2": "beach", | |
| "3": "building_site", | |
| "4": "factory", | |
| "5": "house", | |
| "6": "office", | |
| "7": "road", | |
| "8": "skatepart", | |
| "9": "warehouse" | |
| }, | |
| "image_size": 224, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "airport": "0", | |
| "bathroom": "1", | |
| "beach": "2", | |
| "building_site": "3", | |
| "factory": "4", | |
| "house": "5", | |
| "office": "6", | |
| "road": "7", | |
| "skatepart": "8", | |
| "warehouse": "9", | |
| "zoo": "10" | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "model_type": "vit", | |
| "num_attention_heads": 12, | |
| "num_channels": 3, | |
| "num_hidden_layers": 12, | |
| "patch_size": 16, | |
| "problem_type": "single_label_classification", | |
| "qkv_bias": true, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.31.0" | |
| } | |