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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:
        print(t.name, t.shape, t.dtype)

    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

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.

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The following attestation bundles were made for ztensor-2.0.0-cp39-cp39-macosx_10_12_x86_64.whl:

Publisher: release.yml on pie-project/ztensor

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Release history Release notifications | RSS feed

2.1.2

21 files

2.1.1

21 files

2.1.0

21 files

This release

2.0.0 This release

21 files

1.2.3

34 files

1.2.2

34 files

1.2.1

34 files

1.2.0

34 files

1.1.1

14 files

1.0.2

14 files

1.0.1

14 files

1.0.0

14 files

0.1.4

15 files

0.1.2

15 files

0.1.1

15 files

0.1.0

15 files

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