Offline and on-premises use¶

synapse-sr never needs the network for processing. The only network access is the one-time download of the weights by Pro.from_pretrained(), and that is skipped when you pass a local file.

Air-gapped machines¶

On a connected machine, download the checkpoint from Hugging Face and build a wheelhouse:
```
pip download synapse-sr -d wheelhouse
```

Copy wheelhouse/ and the .safetensors file to the target machine, then:

pip install --no-index --find-links wheelhouse synapse-sr
synapse-sr scene.tif scene_2m.tif --weights /opt/models/synapse-pro-v2.safetensors

import synapse_sr

from synapse_sr import Pro
model = Pro.from_pretrained(weights="/opt/models/synapse-pro-v2.safetensors")

Cache¶

Downloaded weights are stored in ~/.cache/synapse, or in $SYNAPSE_CACHE if set. They are verified by SHA-256 on every load. A corrupted or tampered file raises an error that names the expected and actual hashes.

Your own checkpoints¶

from synapse_sr import Pro
model = Pro.from_pretrained()

model.save_pretrained("my-model.safetensors")         # model + sensor operator in one file
Pro.from_pretrained(weights="my-model.safetensors")