bertcased

Embedded cased English BERT-base NER model package for gonnx/models.

Model

• Open: bertcased.Open(gonnx.WithThreads(1))
• Model adapter: bertcased.BaseCased()
• Source/export: https://huggingface.co/onnx-community/bert-base-NER-ONNX
• Source model: https://huggingface.co/dslim/bert-base-NER
• Upstream ONNX revision packaged: 9faa2f4a2d59b396888b318f596ff719cc893f1e
• Source model revision observed: d1a3e8f13f8c3566299d95fcfc9a8d2382a9affc
• License: MIT per source/export model card at packaging time
• Labels: O, B-MISC, I-MISC, B-PER, I-PER, B-ORG, I-ORG, B-LOC, I-LOC
• Tokenizer: BERT cased WordPiece (vocab.txt), lower-casing disabled
• Max sequence length: 512 tokens including special tokens
• Embedded ONNX asset: quantized ONNX (assets/model_quantized.onnx)

Checksums

b324e829f1fad3b897f926d1a1d1372803c6d04546831a3a2ed103652b916adf  assets/model_quantized.onnx
eeaa9875b23b04b4c54ef759d03db9d1ba1554838f8fb26c5d96fa551df93d02  assets/vocab.txt
e5be6d68d7b6a7af53b759a4b7a3f57332100009ab1e798d70a7c8d8b90dcf3d  assets/config.json

Reproduce assets

./prepare_assets.sh

When to use

Use this model when cased English entity recognition matters and BERT-base runtime/binary cost is acceptable.

Avoid it when you need uncased normalization, smaller binaries, or multilingual/domain-specific labels.