torch.load defaults to weights_only=True since torch 2.6, which rejects
the pickled TrainingArguments dataclass that HF Trainer saves to
training_args.bin. Studio ships on torch 2.9 / 2.10 so this fallback
was already failing on every call, getting swallowed by the surrounding
try/except, and falling through to the existing adapter_config.json /
config.json / directory-name paths that already produce the answer.
In get_base_model_from_lora the path is also reachable via the
GET /loras/{lora_path:path}/base-model route on user-supplied paths
(including third-party LoRAs pulled from HF), so "fixing" it with
weights_only=False would re-introduce a pickle deserialization sink
on remote-supplied input.
Comment both blocks out and leave a TODO so the intent is preserved
for whoever wants to re-enable this with proper safe_globals or a
trust check.
|
||
|---|---|---|
| .. | ||
| datasets | ||
| hardware | ||
| inference | ||
| models | ||
| paths | ||
| .gitkeep | ||
| __init__.py | ||
| _studio_release_build.py | ||
| cache_cleanup.py | ||
| downsample.py | ||
| native_path_leases.py | ||
| studio_version.py | ||
| subprocess_compat.py | ||
| transformers_version.py | ||
| update_status.py | ||
| utils.py | ||
| wheel_utils.py | ||