ztensor
Read any tensor format, write canonical .zt.
pip install ztensor
import ztensor, torch
with ztensor.open("model.safetensors") as src: # or open([shard1, shard2])
for t in src.values(): # src itself is a mapping,
print(t.name, t.shape, t.dtype) # so iterating it gives names
t = src["model.layers.0.mlp.w"]
w = torch.from_dlpack(t) # zero-copy
t.location # (path, offset, nbytes) for your own I/O
t["scales"] # parts are tensors too
A tensor with one part answers about that part. A tensor with several, a quantized one or a CSR one, does not pick for you: index the part you mean.
Reads .zt, .safetensors, .gguf, .npz, PyTorch .pt, HDF5 and ONNX,
detected by magic. Writes exactly one format: canonical .zt, where every
tensor starts on a 64 KiB page and carries an XXH3 digest.
No framework modules
Tensors export DLPack and the buffer protocol, so numpy, torch and jax read them zero-copy without this package knowing any of them exist:
numpy.from_dlpack(t)
torch.from_dlpack(t)
memoryview(t)
DLPack also carries bfloat16, which the numpy dtype table cannot, so the
dtype most checkpoints are actually in survives the trip.
A zero-copy export keeps the mapping alive on its own: an array stays valid after the source it came from is closed.
It tells you what it can do
t.caps.map # a zero-copy export will work
t.caps.locate # .location gives the exact byte range
t.caps.evict # its pages are its own
t.caps.verify # there is a digest to check
Each is the precondition of the operation it names, so the report cannot
disagree with the behaviour. When only metadata is wanted, ztensor.index()
opens without mapping: names, shapes and addresses, for the cost of a header
read.
Converting
ztensor.convert("model.safetensors", "model.zt")
ztensor.verify("model.zt", deep=True) # (digest_verified, without_digests)
Conversion is the upgrade path: the foreign file has no digests and arbitrary alignment; the result has both.
The numpy shim
ztensor.numpy.load_file / save_file are a safetensors-shaped convenience
layer, kept for code written against that API. New code should use the tensor
handles above, which can say things a dict of arrays cannot.
Linux and macOS. MIT licensed. The format, the Rust crates and the specification live at github.com/pie-project/ztensor.
Release files for ztensor 2.1.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| ztensor-2.1.2.tar.gz | 165.1 kB | With provenance | Details for ztensor-2.1.2.tar.gz |
Built distributions (wheels)
Total release size: 21.4 MB
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