Instructions to use ongp/Pacc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ongp/Pacc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ongp/Pacc") 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("ongp/Pacc") model = AutoModelForImageClassification.from_pretrained("ongp/Pacc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from ongp/Pacc: direct link, hf CLI and curl.
- Browser
- Download file 1.03 kB
-
https://huggingface.co/ongp/Pacc/resolve/main/config.json
- Command line
-
hf download hf://ongp/Pacc/config.json
-
curl -L -o config.json https://huggingface.co/ongp/Pacc/resolve/main/config.json
1.03 kB
| { | |
| "_name_or_path": "AutoTrain", | |
| "architectures": [ | |
| "SwinForImageClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.0, | |
| "depths": [ | |
| 2, | |
| 2, | |
| 18, | |
| 2 | |
| ], | |
| "drop_path_rate": 0.1, | |
| "embed_dim": 128, | |
| "encoder_stride": 32, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.0, | |
| "hidden_size": 1024, | |
| "id2label": { | |
| "0": "bbw", | |
| "1": "chubby", | |
| "2": "ssbbw", | |
| "3": "thin", | |
| "4": "ussbbw" | |
| }, | |
| "image_size": 224, | |
| "initializer_range": 0.02, | |
| "label2id": { | |
| "bbw": "0", | |
| "chubby": "1", | |
| "ssbbw": "2", | |
| "thin": "3", | |
| "ussbbw": "4" | |
| }, | |
| "layer_norm_eps": 1e-05, | |
| "max_length": 128, | |
| "mlp_ratio": 4.0, | |
| "model_type": "swin", | |
| "num_channels": 3, | |
| "num_heads": [ | |
| 4, | |
| 8, | |
| 16, | |
| 32 | |
| ], | |
| "num_layers": 4, | |
| "padding": "max_length", | |
| "patch_size": 4, | |
| "path_norm": true, | |
| "problem_type": "single_label_classification", | |
| "qkv_bias": true, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.25.1", | |
| "use_absolute_embeddings": false, | |
| "window_size": 7 | |
| } | |