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README.md

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 # ReciFineGold RecipeRoBERTa (Knowledge-Augmented and Entity Type-Specific (KAES) Token Classification with Entity Type Knowledge Type) `recifinegold-reciperoberta-ka-entity-type`
 
-This model is a **RoBERTa-base-uncased** token-classification model trained on **ReciFineGold** for **recipe-focused Named Entity Recognition (NER)** using a **Knowledge-Augmented & Entity Type-Specific (KAES)** formulation.
+This model is a **RoBERTa-base** token-classification model trained on **ReciFineGold** for **recipe-focused Named Entity Recognition (NER)** using a **Knowledge-Augmented & Entity Type-Specific (KAES)** formulation.
 
 In KAES, the model extracts **one entity type at a time** by **prepending a curated knowledge context** (here: a natural-language **entity type prompt**) to the input recipe sentence. This encourages the encoder to focus on spans relevant to the requested entity type, rather than relying only on the sentence’s internal context.
 
 ## What this checkpoint is
 
-- **Backbone:** RoBERTa-base-uncased
+- **Backbone:** RoBERTa-base
 - **Task:** Token classification (BIO-style tagging)
 - **Formulation:** Knowledge-Augmented + Entity Type-Specific (single entity type per run)
 - **Knowledge type:** **Entity Type prompt** (e.g., “FOOD STATE”)