T5-base masked FP32 Core ML encoder
This repository contains a Core ML conversion of the encoder from
google-t5/t5-base at the exact
source revision:
a9723ea7f1b39c1eae772870f3b547bf6ef7e6c1
The conversion keeps the explicit T5 attention mask and zeros output positions
whose mask value is zero. It uses a fixed 64-token interface for local iOS and
macOS inference.
Artifact
StableAudioT5EncoderMaskedFP32.mlpackage.zip
- Inputs:
input_ids: Int32 [1, 64]attention_mask: Int32 [1, 64], with 1 for valid tokens
- Output:
text_embeddings: Float32 [1, 64, 768]
- Storage precision: Float32
- Minimum deployment target: iOS 17 / macOS 14
- Size: 228,196,156 bytes
- SHA-256:
66f69dca44056cfa0b2779a70ffe406d0b31215ff7ebb0161a3b469051ac1975
The artifact filename reflects the downstream interface for which it was
prepared. The repository contains only Google T5-base-derived weights. It does
not contain Stable Audio, Stability AI, DiT, autoencoder, or other audio-model
weights.
Conversion
convert_masked_t5.py downloads only the pinned public T5-base revision,
exports the masked encoder with Core ML Tools, and compares Core ML output with
the PyTorch reference on valid and padded token positions.
The published package records torch==2.2.2 and coremltools==9.0 in its Core
ML metadata. Run conversion on macOS with Python 3.11 and compatible
transformers, numpy, and sentencepiece releases.
License
This T5-only derivative is provided under the Apache License 2.0, matching the
upstream Google T5-base model. Users remain responsible for reviewing the
upstream model card and license.
