Instructions to use surrealgrain/tensorflow-savedmodel-textlinedataset-bypass with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use surrealgrain/tensorflow-savedmodel-textlinedataset-bypass with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy) # See https://github.com/keras-team/tf-keras for more details. from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("surrealgrain/tensorflow-savedmodel-textlinedataset-bypass") - Notebooks
- Google Colab
- Kaggle
File size: 887 Bytes
8e80baa | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | # TensorFlow SavedModel TextLineDataset PoC
This directory contains a restrained proof-of-concept TensorFlow SavedModel for a Huntr MFV submission.
The model reads a controlled local marker file at inference time:
```text
/tmp/tf_savedmodel_textlinedataset_secret.txt
```
It does not perform network access, destructive file writes, or shell command execution.
## Reproduce
```bash
python scripts/generate_tf_savedmodel_textlinedataset_poc.py
printf 'huntr-controlled-secret-line-1\nhuntr-controlled-secret-line-2\n' > /tmp/tf_savedmodel_textlinedataset_secret.txt
python - <<'PY'
import tensorflow as tf
model = tf.saved_model.load("artifacts/tf_savedmodel_textlinedataset_bypass/dataset_read_savedmodel")
print(model.signatures["serving_default"]()["contents"].numpy().decode())
PY
modelscan -p artifacts/tf_savedmodel_textlinedataset_bypass/dataset_read_savedmodel -r json
```
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