Instructions to use adarshcod30/openforensics-ensemble with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use adarshcod30/openforensics-ensemble with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://adarshcod30/openforensics-ensemble") - Notebooks
- Google Colab
- Kaggle
Download leakage_report.json from adarshcod30/openforensics-ensemble: direct link, hf CLI and curl.
- Browser
- Download file 380 Bytes
-
https://huggingface.co/adarshcod30/openforensics-ensemble/resolve/main/leakage_report.json
- Command line
-
hf download hf://adarshcod30/openforensics-ensemble/leakage_report.json
-
curl -L -o leakage_report.json https://huggingface.co/adarshcod30/openforensics-ensemble/resolve/main/leakage_report.json
380 Bytes
| { | |
| "pairs": { | |
| "Train|Validation": { | |
| "shared_images": 0, | |
| "pct_of_smaller": 0.0 | |
| }, | |
| "Train|Test": { | |
| "shared_images": 0, | |
| "pct_of_smaller": 0.0 | |
| }, | |
| "Validation|Test": { | |
| "shared_images": 0, | |
| "pct_of_smaller": 0.0 | |
| } | |
| }, | |
| "leaking": false, | |
| "within_split_duplicates": { | |
| "Train": 0, | |
| "Validation": 0, | |
| "Test": 0 | |
| } | |
| } |