cdlib
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marc-match-ai

pytorch_model_hub_mixin

model_hub_mixin

entity-matching

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RvanB commited on May 2

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 # MARC Record Matching with Bibliographic Metadata
 Traditional matching of MARC (Machine-Readable Cataloging) records has relied heavily on identifiers like OCLC numbers, ISBNs, LCCNs, etc. assigned by catalogers. However, this approach struggles with records having incorrect identifiers or lacking them altogether. This model has been developed to match MARC records based solely on their bibliographic metadata (title, author, publisher, etc.), enabling successful matches even when identifiers are missing or inaccurate.
-Check out the code and dataset at our [GitHub repository](https://github.com/cdlib/marcai).
 Try out our [interactive demo](https://huggingface.co/spaces/cdlib/marc-match-ai-demo) to see the model in action!

 # MARC Record Matching with Bibliographic Metadata
 Traditional matching of MARC (Machine-Readable Cataloging) records has relied heavily on identifiers like OCLC numbers, ISBNs, LCCNs, etc. assigned by catalogers. However, this approach struggles with records having incorrect identifiers or lacking them altogether. This model has been developed to match MARC records based solely on their bibliographic metadata (title, author, publisher, etc.), enabling successful matches even when identifiers are missing or inaccurate.
+Check out the code and dataset at our [GitHub repository](https://github.com/cdlib/marc-ai).
 Try out our [interactive demo](https://huggingface.co/spaces/cdlib/marc-match-ai-demo) to see the model in action!