Instructions to use tanganke/convnext-base-224_resisc45_sgd_batch-size-64_lr-0.01_steps-4000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tanganke/convnext-base-224_resisc45_sgd_batch-size-64_lr-0.01_steps-4000 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="tanganke/convnext-base-224_resisc45_sgd_batch-size-64_lr-0.01_steps-4000") 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("tanganke/convnext-base-224_resisc45_sgd_batch-size-64_lr-0.01_steps-4000") model = AutoModelForImageClassification.from_pretrained("tanganke/convnext-base-224_resisc45_sgd_batch-size-64_lr-0.01_steps-4000", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from tanganke/convnext-base-224_resisc45_sgd_batch-size-64_lr-0.01_steps-4000: direct link, hf CLI and curl.
- Browser
- Download file 2.74 kB
-
https://huggingface.co/tanganke/convnext-base-224_resisc45_sgd_batch-size-64_lr-0.01_steps-4000/resolve/main/config.json
- Command line
-
hf download hf://tanganke/convnext-base-224_resisc45_sgd_batch-size-64_lr-0.01_steps-4000/config.json
-
curl -L -o config.json https://huggingface.co/tanganke/convnext-base-224_resisc45_sgd_batch-size-64_lr-0.01_steps-4000/resolve/main/config.json
2.74 kB
| { | |
| "architectures": [ | |
| "ConvNextForImageClassification" | |
| ], | |
| "depths": [ | |
| 3, | |
| 3, | |
| 27, | |
| 3 | |
| ], | |
| "drop_path_rate": 0.0, | |
| "dtype": "float32", | |
| "hidden_act": "gelu", | |
| "hidden_sizes": [ | |
| 128, | |
| 256, | |
| 512, | |
| 1024 | |
| ], | |
| "id2label": { | |
| "0": "airplane", | |
| "1": "airport", | |
| "2": "baseball diamond", | |
| "3": "basketball court", | |
| "4": "beach", | |
| "5": "bridge", | |
| "6": "chaparral", | |
| "7": "church", | |
| "8": "circular farmland", | |
| "9": "cloud", | |
| "10": "commercial area", | |
| "11": "dense residential", | |
| "12": "desert", | |
| "13": "forest", | |
| "14": "freeway", | |
| "15": "golf course", | |
| "16": "ground track field", | |
| "17": "harbor", | |
| "18": "industrial area", | |
| "19": "intersection", | |
| "20": "island", | |
| "21": "lake", | |
| "22": "meadow", | |
| "23": "medium residential", | |
| "24": "mobile home park", | |
| "25": "mountain", | |
| "26": "overpass", | |
| "27": "palace", | |
| "28": "parking lot", | |
| "29": "railway", | |
| "30": "railway station", | |
| "31": "rectangular farmland", | |
| "32": "river", | |
| "33": "roundabout", | |
| "34": "runway", | |
| "35": "sea ice", | |
| "36": "ship", | |
| "37": "snowberg", | |
| "38": "sparse residential", | |
| "39": "stadium", | |
| "40": "storage tank", | |
| "41": "tennis court", | |
| "42": "terrace", | |
| "43": "thermal power station", | |
| "44": "wetland" | |
| }, | |
| "image_size": 224, | |
| "initializer_range": 0.02, | |
| "label2id": { | |
| "airplane": 0, | |
| "airport": 1, | |
| "baseball diamond": 2, | |
| "basketball court": 3, | |
| "beach": 4, | |
| "bridge": 5, | |
| "chaparral": 6, | |
| "church": 7, | |
| "circular farmland": 8, | |
| "cloud": 9, | |
| "commercial area": 10, | |
| "dense residential": 11, | |
| "desert": 12, | |
| "forest": 13, | |
| "freeway": 14, | |
| "golf course": 15, | |
| "ground track field": 16, | |
| "harbor": 17, | |
| "industrial area": 18, | |
| "intersection": 19, | |
| "island": 20, | |
| "lake": 21, | |
| "meadow": 22, | |
| "medium residential": 23, | |
| "mobile home park": 24, | |
| "mountain": 25, | |
| "overpass": 26, | |
| "palace": 27, | |
| "parking lot": 28, | |
| "railway": 29, | |
| "railway station": 30, | |
| "rectangular farmland": 31, | |
| "river": 32, | |
| "roundabout": 33, | |
| "runway": 34, | |
| "sea ice": 35, | |
| "ship": 36, | |
| "snowberg": 37, | |
| "sparse residential": 38, | |
| "stadium": 39, | |
| "storage tank": 40, | |
| "tennis court": 41, | |
| "terrace": 42, | |
| "thermal power station": 43, | |
| "wetland": 44 | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "layer_scale_init_value": 1e-06, | |
| "model_type": "convnext", | |
| "num_channels": 3, | |
| "num_stages": 4, | |
| "out_features": [ | |
| "stage4" | |
| ], | |
| "out_indices": [ | |
| 4 | |
| ], | |
| "patch_size": 4, | |
| "stage_names": [ | |
| "stem", | |
| "stage1", | |
| "stage2", | |
| "stage3", | |
| "stage4" | |
| ], | |
| "transformers_version": "4.57.3" | |
| } | |