---
license: apache-2.0
base_model: 1-800-BAD-CODE/punct_cap_seg_47_language
tags:
- coreml
- punctuation
- true-casing
- sentence-boundary-detection
---

# punct_cap_seg_47_language, Core ML, fp32

A Core ML conversion of [1-800-BAD-CODE/punct_cap_seg_47_language](https://huggingface.co/1-800-BAD-CODE/punct_cap_seg_47_language):
punctuation, true-casing and sentence boundary detection for 47 languages, in one pass over
lower-cased, unpunctuated text.

Converted from the original ONNX model at commit `1b9d51fc7989ebc61e844d407d9dadd08ff4ba28`
(ONNX → PyTorch with onnx2torch → Core ML with coremltools 8.3) by `conversion/convert.py`,
with the versions in `conversion/requirements.txt`. The weights stay fp32: half precision changes
the predictions. The script checks that the punctuation and sentence ends it predicts match the
ONNX model's.

## Files

- `PunctCapSeg47.mlpackage`: the model. Input `input_ids`, int32 `[1, 128]`: `<s>` (1), the text's
  token ids, `</s>` (2), padded with `<pad>` (3). Outputs, one per token:
  - `pre_preds`, `post_preds`: indices into `pre_labels` and `post_labels` of the original
    `config.yaml` — the mark before and after the token;
  - `cap_preds` (`[1, 128, 16]`): 1 where that character of the token is upper case;
  - `seg_preds`: 1 where a sentence ends after the token.
- `vocab.json`: the SentencePiece unigram vocabulary (piece, score, type) of
  `spe_unigram_64k_lowercase_47lang.model`, and the special ids.
- `ORIGINAL_README.md`: the original model card.
- `conversion/convert.py`, `conversion/requirements.txt`: the conversion.

## License

Apache 2.0, as the original model. All credit for the model goes to its author.