AI model formats¶
Use this when you want to know exactly which AI/ML model file formats
loom model reads, which optional dependency each one needs, and what
Pitloom actually pulls out of the file.
Quick guide¶
pip install "pitloom[ai]"
loom model path/to/model.safetensors -o model.spdx3.json
loom model auto-detects the format from the file itself, not just the
extension.
Supported formats¶
| Format | Extension(s) | Install extra |
|---|---|---|
| fastText | .ftz, .bin |
pip install fasttext |
| GGUF | .gguf |
pip install gguf |
| HDF5 / Keras v1-v2 | .h5, .hdf5 |
pip install h5py |
| Keras v3 | .keras |
(none -- stdlib only) |
| NumPy | .npy, .npz |
pip install numpy |
| ONNX | .onnx |
pip install onnx |
| PyTorch classic | .pt, .pth |
pip install fickling (safe pickle inspection) |
| PyTorch PT2 / ExecuTorch | .pt2 |
(none -- stdlib only) |
| Safetensors | .safetensors |
pip install safetensors |
pip install "pitloom[ai]" pulls in every optional dependency above at
once; install a single extractor's package directly if you only need one
format.
Every extraction is read-only and inspects the file's own structure
(binary header, ZIP archive contents, or safe AST inspection of a pickle)
-- Pitloom never executes model code or calls pickle.load().
Hugging Face Hub models¶
Pass a Hugging Face Hub URL or a bare model ID instead of a local file --
no download required for the SBOM itself (needs
pip install pitloom[huggingface_hub]):
loom model https://huggingface.co/mistralai/Mistral-7B-v0.1
loom model Qwen/Qwen3-235B-A22B
This reads the model card, config.json, tokenizer_config.json, and
generation_config.json from the Hub API and produces an enriched
ai_AIPackage.
Not yet supported¶
JAX (Orbax), TensorFlow SavedModel, TensorFlow Lite, and scikit-learn (pickle/joblib) are on the roadmap but not implemented yet.
See also¶
- Command line -- the
loom modelcommand in context with Pitloom's other generation targets. - Python API --
generate_model_sbom(), the equivalent entry point from Python code.