d1-omni-600M, now running on Apple silicon with Core ML ⚡
We pointed it at a firehose of 5,000 real comments from Civil Comments with GPU + ANE. moderating 224 comments/s on an M5 Pro.
95.4% agreement with human raters, same as the base PyTorch too.
🤗 Model:
🛠️ SDK:
Show more
We have converted GLiNER2.5-Decide to coreml. ~4× faster, ~5× less Peak RAM, half the size.
model:
code:
Thanks for the model, we were able to port Laya to coreml with 99.5% of the ops on ANE + benchmarked too. it is now blazing fast with 3.7 ms per decision on an M5 Pro.
Release:
Models:
Show more
