Token Classification
GLiFormer
PyTorch
English
deberta
named-entity-recognition
text-classification
relation-extraction
structured-extraction
feature-extraction
document-understanding
Instructions to use knowledgator/gliformer-large-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- GLiFormer
How to use knowledgator/gliformer-large-v1 with GLiFormer:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
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- structured-extraction
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# GLiFormer Large v1
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- Extraction can omit information, choose incorrect spans, or attach records to the wrong parent.
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- Reported NER transfer groups do not establish that every evaluated domain was absent from training.
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- Fixed record anchors and the configured span width constrain extraction capacity.
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- This checkpoint has no dedicated vision, audio, or open relation head.
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- structured-extraction
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- feature-extraction
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- document-understanding
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license: apache-2.0
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---
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# GLiFormer Large v1
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- Extraction can omit information, choose incorrect spans, or attach records to the wrong parent.
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| 317 |
- Reported NER transfer groups do not establish that every evaluated domain was absent from training.
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| 318 |
- Fixed record anchors and the configured span width constrain extraction capacity.
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- This checkpoint has no dedicated vision, audio, or open relation head.
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