v1.2.66 - CPU offload H3 & bugfixes
What's Changed
Installer fixes
Install failed on older uv. We were passing a flag that only exists in uv 0.10 and newer, so anyone with an older uv saw unexpected argument '--no-sources-package' and the install stopped before downloading anything. Fixed, and it now works back to uv 0.4.
Large model downloads failed. The 66GB MiniMax H3 transformer could not be fetched at all: The file is too large to be downloaded using the regular download method. Hugging Face needs the hf_xet package for files that size, and our dependency floor was old enough that it was not getting installed. Fixed for fresh installs.
If you are on an existing venv and hit this, install it yourself:
cd Inline-Studio\core
uv pip install --python .venv\Scripts\python.exe hf_xet
Trainer fixes
CPU offload did nothing on MiniMax H3. The setting was in the panel but silently ignored, because we skipped it for any 4-bit base and H3 is always 4-bit. That was backwards: H3's base is small and it is the clip activations that fill the card, so this is exactly the model that needs it. Setting it to On now works.
The status said the wrong thing. Progress only updated after a step finished, so the UI showed loading model (nf4) for the whole of the first step. A slow first step looked like a stuck loader. It now says training before step one starts.
Better memory logging. The trainer now prints allocated and reserved VRAM after caching, after the base loads, and entering the loop, so a slow run can be diagnosed from the log.
Upgrading
The app reads its version from Core's installed metadata, so reinstall or it keeps showing the old one:
cd core && uv pip install --python .venv/bin/python -e . --no-deps
Full Changelog: v1.2.65...v1.2.66
What's Changed
Full Changelog: v1.2.65...v1.2.66
