content.raw: For anyone who struggles with NER or information extraction with LLM.
content.type: text
content.value: For anyone who struggles with NER or information extraction with LLM.
content.type: new_line
content.type: new_line
content.raw: We showed an efficient workflow for token classification including zero-shot suggestions and model fine-tuning with Argilla, GliNER, the NuMind NuExtract LLM and SpanMarker. 
content.type: text
content.value: We showed an efficient workflow for token classification including zero-shot suggestions and model fine-tuning with Argilla, GliNER, the NuMind NuExtract LLM and SpanMarker. 
content.raw: @argilla
content.type: mention
content.user: argilla
content.type: new_line
content.type: new_line
content.raw: Video: 
content.type: text
content.value: Video: 
content.href: https://youtu.be/JvLpaYgNd84?feature=shared
content.raw: https://youtu.be/JvLpaYgNd84?feature=shared
content.type: link
content.type: new_line
content.raw: Notebooks and slides included to try it yourself 🙂 
content.type: text
content.value: Notebooks and slides included to try it yourself 🙂 
rawContent: For anyone who struggles with NER or information extraction with LLM.
  
  We showed an efficient workflow for token classification including zero-shot suggestions and model fine-tuning with Argilla, GliNER, the NuMind NuExtract LLM and SpanMarker. @argilla
  
  Video: https://youtu.be/JvLpaYgNd84?feature=shared
  Notebooks and slides included to try it yourself 🙂 
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