openfoodfacts
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spellcheck-mistral-7b

Text Generation

text-generation-inference

Inference Endpoints

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jeremyarancio commited on 22 days ago

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@@ -72,7 +72,7 @@ The model is evaluated on the [benchmark](https://huggingface.co/datasets/openfo
 In short, lists of ingredients are separated into 3 parts: *original*, *reference*, *prediction*. Using a [sequence alignement algorithm](https://en.wikipedia.org/wiki/Sequence_alignment) between respectively *original*-*reference* and *original*-**prediction*, we are able to tell which token were supposed to be corrected, and which one was actually corrected. This leads to a correction Precision and Recall.
-The complete explanation of the algorithm is available in the [Spellchech README](https://github.com/openfoodfacts/openfoodfacts-ai/tree/spellcheck/spellcheck).
 ### Metrics:
 * Correction precision: **0.67**

 In short, lists of ingredients are separated into 3 parts: *original*, *reference*, *prediction*. Using a [sequence alignement algorithm](https://en.wikipedia.org/wiki/Sequence_alignment) between respectively *original*-*reference* and *original*-**prediction*, we are able to tell which token were supposed to be corrected, and which one was actually corrected. This leads to a correction Precision and Recall.
+The complete explanation of the algorithm is available in the [Spellchech README](https://github.com/openfoodfacts/openfoodfacts-ai/tree/develop/spellcheck#-evaluation-metrics-and-algorithm).
 ### Metrics:
 * Correction precision: **0.67**