ReciFineGold RecipeBERT (Traditional Token Classification) recifinegold recipebert trad This model is a BERT base uncased token classification model trained on ReciFineGold for recipe focused Named Entity Recognition (NER) . What this checkpoint is Backbone: BERT base uncased Task: Token classification (BIO style tagging) How to use The ReciFine library provides a lightweight inference wrapper ( ReciFineNER ) that handles extraction and decoding. Quick links (documentation + notebook) ReciFine library (recommended): training scripts, inference wrappers, and full documentation https://github.com/nuhu ibrahim/ReciFine/tree/main Colab (end to end usage demo): https://colab.research.google.com/drive/1CatH2YOhnOWf VglprEgxONWRkrXRBXo?usp=sharing&authuser=1 Intended use Use this model to extract fine grained recipe entities from procedural recipe text (e.g., instructions), including ingredients, tools, quantities, durations, actions, and state descriptors. Typical applications: Structured parsing of recipe steps Ingredient and action extraction for downstream cooking assistants Data normalisation and indexing for recipe search Entity aware prompting and evaluation pipelines for recipe ge…
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