Views
No views yet
| ID | Label | Description |
|---|---|---|
| 0 | O | Outside any entity |
| 1 | B-MISC | Beginning of miscellaneous entity |
| 2 | I-MISC | Inside miscellaneous entity |
| 3 | B-PER | Beginning of person name |
| 4 | I-PER | Inside person name |
| 5 | B-ORG | Beginning of organization |
| 6 | I-ORG | Inside organization |
| 7 | B-LOC | Beginning of location |
| 8 | I-LOC | Inside location |
| File | Format | Size |
|---|---|---|
bert-base-ner-f32.gguf | Float32 | 412 MB |
bert-base-ner-q8_0.gguf | Q8_0 | 111 MB |
bert-base-ner-q4_k.gguf | Q4_K | 70 MB |
crispembed -m bert-base-ner-q8_0.gguf --ner "Barack Obama was born in Hawaii"1from crispembed import CrispNER
2ner = CrispNER("bert-base-ner-q8_0.gguf")
3entities = ner.extract("Barack Obama was born in Hawaii")
4# [{"text": "Barack Obama", "label": "PER", "start": 0, "end": 12, "score": 0.999},
5# {"text": "Hawaii", "label": "LOC", "start": 25, "end": 31, "score": 1.000}]ner.classifier.weight in GGUF.dslim.mit. This repository redistributes under the same terms; it grants no rights the upstream licence does not.