Instructions to use kolkela/simple-cnn-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use kolkela/simple-cnn-classifier with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://kolkela/simple-cnn-classifier") - Notebooks
- Google Colab
- Kaggle
| { | |
| "classification_report": { | |
| "glass": { | |
| "precision": 0.6923076923076923, | |
| "recall": 0.6428571428571429, | |
| "f1-score": 0.6666666666666666, | |
| "support": 42.0 | |
| }, | |
| "metal": { | |
| "precision": 0.6195652173913043, | |
| "recall": 0.7215189873417721, | |
| "f1-score": 0.6666666666666666, | |
| "support": 79.0 | |
| }, | |
| "organic": { | |
| "precision": 0.7613636363636364, | |
| "recall": 0.7790697674418605, | |
| "f1-score": 0.7701149425287356, | |
| "support": 86.0 | |
| }, | |
| "paper": { | |
| "precision": 0.7586206896551724, | |
| "recall": 0.6804123711340206, | |
| "f1-score": 0.717391304347826, | |
| "support": 97.0 | |
| }, | |
| "plastic": { | |
| "precision": 0.6483516483516484, | |
| "recall": 0.6344086021505376, | |
| "f1-score": 0.6413043478260869, | |
| "support": 93.0 | |
| }, | |
| "accuracy": 0.6952141057934509, | |
| "macro avg": { | |
| "precision": 0.6960417768138908, | |
| "recall": 0.6916533741850668, | |
| "f1-score": 0.6924287856071965, | |
| "support": 397.0 | |
| }, | |
| "weighted avg": { | |
| "precision": 0.6986971238573397, | |
| "recall": 0.6952141057934509, | |
| "f1-score": 0.6955284951982446, | |
| "support": 397.0 | |
| } | |
| }, | |
| "confusion_matrix": [ | |
| [ | |
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| } |