| --- |
| license: mit |
| base_model: urchade/gliner_multi-v2.1 |
| pipeline_tag: token-classification |
| library_name: onnx |
| language: |
| - multilingual |
| tags: |
| - ner |
| - gliner |
| - onnx |
| --- |
| |
| # ONNX - gliner_multi-v2.1 |
| FP32 = model.onnx |
| |
| INT8 = model_quantized.onnx |
|
|
| ## Usage |
|
|
| ``` |
| # onnxruntime-gpu for run it on GPU |
| pip install onnxruntime sentencepiece numpy protobuf |
| ``` |
|
|
| - [src/helper.py](src/helper.py) = onnx session builder (provider selection, threads, memory options) |
| - [src/example.py](src/example.py) = full pipeline: word split, sentencepiece tokenization, span enumeration, inference, greedy non-overlap selection |
|
|
| ``` |
| python3 src/example.py |
| ``` |
|
|
| ``` |
| 0.970778 | person | Linus Torvalds |
| 0.603953 | organization | Linux |
| 0.978727 | place | Helsinki |
| 0.859634 | organization | Linux Foundation |
| 0.944801 | person | 田中太郎 |
| 0.674417 | organization | 東京大学 |
| 0.953844 | place | Tokyo |
| ``` |
|
|
| Note: |
| - No transformers/tokenizers dependency: the tokenizer is `spm.model` loaded via proto with the patch<br> |
| `normalizer_spec.add_dummy_prefix = False` (required for the word-level alignment). |
| - Entity types are free text, passed in the input sequence:<br> |
| `[cls] [ent] type... [ent] type... [sep] word... [eos]`, with `[ent]` = 250103, `[sep]` = 250104. |
| - `words_mask` marks the first subword of each word with the word number (1-based), 0 elsewhere. |
| - Digits are tokenized one at a time (`\d|\D+`), CJK characters are split one word each. |
| - Spans are enumerated per word up to width 12, score = sigmoid(logit), greedy selection without overlap. |
| - Normalize input with NFKC for consistent multilingual scores. |
|
|
