| [日本語](README.md) | |
| # SBV2 Core ML shared model: original FP32 (float32) | |
| This folder contains the **original FP32 (float32)** shared BERT and Open JTalk dictionary, approximately 1.52 GB. | |
| BERT uses the original unquantized FP32 weights. BERT computation and tensor interfaces remain FP32. | |
| Supply a separate compatible voice model. Both shared variants use the same voice models. | |
| ## Download and use | |
| Choose this variant's `download.json` from the [model selection table](https://huggingface.co/AILogDev/sbv2-coreml-common). | |
| If downloading folders, select this `float32/` root in the sample's **モデル設定 → 共通モデル**, then press **モデルを準備**. | |
| For the SDK, pass its `bert/` and `dictionary/` subfolders and a separate voice folder. | |
| Compilation caches require additional storage. | |
| ## Attribution and license | |
| BERT derives from Kyoto University's NLP group's [Japanese DeBERTa](https://huggingface.co/ku-nlp/deberta-v2-large-japanese-char-wwm). | |
| See this folder's `LICENSE.md` for CC BY-SA 4.0 terms and `dictionary/COPYING` for separate dictionary terms. | |
| Provenance is in `provenance.json`; file hashes are in `checksums.json`. | |
| This unofficial conversion is not endorsed by the original authors. | |
| This is the original converted Core ML BERT without the INT8 weight quantization, not the PyTorch checkpoint. | |