Image Classification
Transformers
PyTorch
TensorBoard
beit
Generated from Trainer
Eval Results (legacy)
Instructions to use ChasingMercer/weather-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ChasingMercer/weather-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ChasingMercer/weather-base") 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("ChasingMercer/weather-base") model = AutoModelForImageClassification.from_pretrained("ChasingMercer/weather-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from ChasingMercer/weather-base: direct link, hf CLI and curl.
- Browser
- Download file 1.57 kB
-
https://huggingface.co/ChasingMercer/weather-base/resolve/main/config.json
- Command line
-
hf download hf://ChasingMercer/weather-base/config.json
-
curl -L -o config.json https://huggingface.co/ChasingMercer/weather-base/resolve/main/config.json
1.57 kB
| { | |
| "_name_or_path": "microsoft/beit-base-patch16-224-pt22k-ft22k", | |
| "architectures": [ | |
| "BeitForImageClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.0, | |
| "auxiliary_channels": 256, | |
| "auxiliary_concat_input": false, | |
| "auxiliary_loss_weight": 0.4, | |
| "auxiliary_num_convs": 1, | |
| "drop_path_rate": 0.1, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.0, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "dew", | |
| "1": "fogsmog", | |
| "2": "frost", | |
| "3": "glaze", | |
| "4": "hail", | |
| "5": "lightning", | |
| "6": "rain", | |
| "7": "rainbow", | |
| "8": "rime", | |
| "9": "sandstorm", | |
| "10": "snow" | |
| }, | |
| "image_size": 224, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "dew": 0, | |
| "fogsmog": 1, | |
| "frost": 2, | |
| "glaze": 3, | |
| "hail": 4, | |
| "lightning": 5, | |
| "rain": 6, | |
| "rainbow": 7, | |
| "rime": 8, | |
| "sandstorm": 9, | |
| "snow": 10 | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "layer_scale_init_value": 0.1, | |
| "model_type": "beit", | |
| "num_attention_heads": 12, | |
| "num_channels": 3, | |
| "num_hidden_layers": 12, | |
| "out_indices": [ | |
| 3, | |
| 5, | |
| 7, | |
| 11 | |
| ], | |
| "patch_size": 16, | |
| "pool_scales": [ | |
| 1, | |
| 2, | |
| 3, | |
| 6 | |
| ], | |
| "problem_type": "single_label_classification", | |
| "semantic_loss_ignore_index": 255, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.26.1", | |
| "use_absolute_position_embeddings": false, | |
| "use_auxiliary_head": true, | |
| "use_mask_token": false, | |
| "use_mean_pooling": true, | |
| "use_relative_position_bias": true, | |
| "use_shared_relative_position_bias": false, | |
| "vocab_size": 8192 | |
| } | |