Instructions to use fsabiu/keras-modelscan-torchmodulewrapper-coverage-gap with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use fsabiu/keras-modelscan-torchmodulewrapper-coverage-gap with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://fsabiu/keras-modelscan-torchmodulewrapper-coverage-gap") - Notebooks
- Google Colab
- Kaggle
File size: 808 Bytes
496e58e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | # EXP-MFV-20260502-002 Summary
| File | Detector findings | ModelScan issues | Gap |
| --- | ---: | ---: | --- |
| `benign_dense.keras` | `0` | `0` | `no` |
| `benign_external_vocab_lookup.keras` | `0` | `0` | `no` |
| `benign_functional.keras` | `0` | `0` | `no` |
| `benign_lambda.keras` | `2` | `1` | `no` |
| `benign_registered_custom.keras` | `0` | `0` | `no` |
| `benign_torch_module.keras` | `1` | `0` | `yes` |
## Detector Findings
### `benign_lambda.keras`
- `unsafe_class` at `$.config.layers[1]`: Lambda layer may deserialize Python functions/lambdas.
- `serialized_lambda` at `$.config.layers[1].config.function`: Serialized Python lambda object.
### `benign_torch_module.keras`
- `unsafe_class` at `$.config.layers[1]`: TorchModuleWrapper may deserialize torch.nn.Module via torch.load().
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