Instructions to use Promemoria/wool-classifier-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Promemoria/wool-classifier-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Promemoria/wool-classifier-finetuned") 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("Promemoria/wool-classifier-finetuned") model = AutoModelForImageClassification.from_pretrained("Promemoria/wool-classifier-finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from Promemoria/wool-classifier-finetuned: direct link, hf CLI and curl.
- Browser
- Download file 1.05 kB
-
https://huggingface.co/Promemoria/wool-classifier-finetuned/resolve/main/config.json
- Command line
-
hf download hf://Promemoria/wool-classifier-finetuned/config.json
-
curl -L -o config.json https://huggingface.co/Promemoria/wool-classifier-finetuned/resolve/main/config.json
1.05 kB
| { | |
| "architectures": [ | |
| "ViTForImageClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.0, | |
| "encoder_stride": 16, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.0, | |
| "hidden_size": 1024, | |
| "id2label": { | |
| "0": "CHECK - V", | |
| "1": "GESSATI - V", | |
| "2": "MICRO EFFETTI - V", | |
| "3": "PIED DE POULE - V", | |
| "4": "PRINCIPE DI GALLES - V", | |
| "5": "QUADRETTO - V", | |
| "6": "SPIGA - V", | |
| "7": "UNITI" | |
| }, | |
| "image_size": 224, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 4096, | |
| "label2id": { | |
| "CHECK - V": 0, | |
| "GESSATI - V": 1, | |
| "MICRO EFFETTI - V": 2, | |
| "PIED DE POULE - V": 3, | |
| "PRINCIPE DI GALLES - V": 4, | |
| "QUADRETTO - V": 5, | |
| "SPIGA - V": 6, | |
| "UNITI": 7 | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "model_type": "vit", | |
| "num_attention_heads": 16, | |
| "num_channels": 3, | |
| "num_hidden_layers": 24, | |
| "patch_size": 16, | |
| "pooler_act": "tanh", | |
| "pooler_output_size": 1024, | |
| "problem_type": "single_label_classification", | |
| "qkv_bias": true, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.55.4" | |
| } | |