Float16 conversions of Stability AI's Stable Audio 3
checkpoints, repackaged for the Windows build of SA3 Variations.
These are Stability AI's models. This repo is a redistribution, not a new
model, and is not affiliated with or endorsed by Stability AI.
Why this exists
The SA3 Variations Windows app runs inference through PyTorch and needs its
weights on disk at install time. The upstream repos are gated, which would mean
every user creating a Hugging Face account and a token just to install a
desktop app. This repo removes that step.
What was changed
Converted with scripts/convert_weights_fp16.py:
every float32/float64 tensor cast to float16. Integer indices, masks and bools
are untouched, and the bundled T5Gemma text encoder is left in bfloat16 —
bf16 to fp16 narrows exponent range and risks overflow.
This is a storage change, not a quality one: the app loads with
model_half=True on CUDA, so these weights were being cast to fp16 at load
anyway. Verified by generating identical seeds from the original fp32 model and
this conversion:
corr(fp32, fp16) = +1.000000 (3 seeds)
upstream fp32
here
medium/model.safetensors
9.22 GB
4.3 GB
medium/t5gemma-b-b-ul2/
1.18 GB
unchanged (bf16)
Layout
Each directory is self-contained — checkpoint, config, and its own copy of the
text encoder, so the app can load it with a local path and no network access:
