Instructions to use hf-tiny-model-private/tiny-random-PoolFormerForImageClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-PoolFormerForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-tiny-model-private/tiny-random-PoolFormerForImageClassification") 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("hf-tiny-model-private/tiny-random-PoolFormerForImageClassification") model = AutoModelForImageClassification.from_pretrained("hf-tiny-model-private/tiny-random-PoolFormerForImageClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from hf-tiny-model-private/tiny-random-PoolFormerForImageClassification: direct link, hf CLI and curl.
- Browser
- Download file 727 Bytes
-
https://huggingface.co/hf-tiny-model-private/tiny-random-PoolFormerForImageClassification/resolve/2f1b23d966d5d3f5a170b7832cf74b9725fd0ed5/config.json
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-PoolFormerForImageClassification@2f1b23d966d5d3f5a170b7832cf74b9725fd0ed5/config.json
-
curl -L -o config.json https://huggingface.co/hf-tiny-model-private/tiny-random-PoolFormerForImageClassification/resolve/2f1b23d966d5d3f5a170b7832cf74b9725fd0ed5/config.json
727 Bytes
| { | |
| "architectures": [ | |
| "PoolFormerForImageClassification" | |
| ], | |
| "depths": [ | |
| 2, | |
| 2, | |
| 2, | |
| 2 | |
| ], | |
| "drop_path_rate": 0.0, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_sizes": [ | |
| 16, | |
| 32, | |
| 64, | |
| 128 | |
| ], | |
| "image_size": 64, | |
| "initializer_range": 0.02, | |
| "layer_scale_init_value": 1e-05, | |
| "mlp_ratio": 4.0, | |
| "model_type": "poolformer", | |
| "num_channels": 3, | |
| "num_encoder_blocks": 4, | |
| "padding": [ | |
| 2, | |
| 1, | |
| 1, | |
| 1 | |
| ], | |
| "patch_size": 16, | |
| "patch_sizes": [ | |
| 7, | |
| 3, | |
| 3, | |
| 3 | |
| ], | |
| "pool_size": 3, | |
| "stride": 16, | |
| "strides": [ | |
| 4, | |
| 2, | |
| 2, | |
| 2 | |
| ], | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.28.0.dev0", | |
| "use_layer_scale": true | |
| } | |