adisyonist
/

14-allergens-0.3b

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 ---
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 ---
 library_name: transformers
+tags:
+  - food
+  - menu-understanding
+  - allergen-detection
+  - text-classification
+language:
+  - en
+  - tr
+  - bn
+  - ca
+  - hr
+  - cs
+  - da
+  - nl
+  - fi
+  - fr
+  - de
+  - el
+  - gu
+  - he
+  - hi
+  - hu
+  - id
+  - it
+  - ja
+  - kn
+  - ko
+  - ms
+  - ml
+  - mr
+  - nb
+  - or
+  - pl
+  - pt
+  - pa
+  - ro
+  - ru
+  - sk
+  - sl
+  - es
+  - sv
+  - ta
+  - te
+  - th
+  - uk
+  - ur
+  - vi
+  - zh
 ---
+# 14-Allergens 0.3B
+## English
+### Overview
+14-Allergens is a multilingual food and menu understanding model for identifying allergen information in short menu descriptions. It is designed to support restaurant software, menu normalization, recipe search, and food-data prototyping.
+The associated training data contains menu and food text paired with labels from a 14-allergen vocabulary. The current data release contains 131,825 JSONL records and is available at [adisyonist/14-allergens](https://huggingface.co/datasets/adisyonist/14-allergens).
+Model repository: [adisyonist/14-allergens-0.3b](https://huggingface.co/adisyonist/14-allergens-0.3b)
+### Allergen vocabulary
+The labels are: `celery`, `crustaceans`, `eggs`, `fish`, `gluten`, `lupin`, `milk`, `mollusks`, `mustard`, `nuts`, `peanuts`, `sesame`, `soy`, and `sulfites`.
+### Intended use
+- Extracting or classifying likely allergens from menu text
+- Assisting menu translation, normalization, and search
+- Prototyping food-safety and restaurant-service applications
+- Providing candidate labels for human review
+### Limitations and safety
+The model and data may contain errors, omissions, translation artifacts, and recipe-specific differences. Predictions are not medical advice and must not be used as the sole basis for allergy, food-safety, restaurant-service, or health decisions. Ingredients, preparation methods, and cross-contact information must be verified by qualified professionals before real-world use. No benchmark results are claimed in this model card.
+### Training and evaluation
+The exact base architecture, hyperparameters, compute resources, and evaluation metrics depend on the training run used to publish this model and are not specified here. Users should evaluate the model on representative, independently reviewed data before deployment.
+### License and attribution
+Review the repository files and the dataset card for the applicable license and source details before redistribution or commercial use.
+## Türkçe
+### Genel bakış
+14-Allergens, kısa menü açıklamalarındaki alerjen bilgilerini belirlemeye yardımcı olmak için hazırlanmış çok dilli bir yiyecek ve menü anlama modelidir. Restoran yazılımları, menü normalizasyonu, tarif arama ve gıda verisi prototipleme çalışmalarında kullanılmak üzere tasarlanmıştır.
+İlişkili eğitim verileri, yiyecek ve menü metinlerini 14 alerjenlik bir etiket sözlüğüyle eşleştirir. Mevcut veri sürümü 131.825 JSONL kaydı içerir ve [adisyonist/14-allergens](https://huggingface.co/datasets/adisyonist/14-allergens) adresinde bulunur.
+Model deposu: [adisyonist/14-allergens-0.3b](https://huggingface.co/adisyonist/14-allergens-0.3b)
+### Alerjen sözlüğü
+Etiketler şunlardır: `celery` (kereviz), `crustaceans` (kabuklular), `eggs` (yumurta), `fish` (balık), `gluten` (gluten), `lupin` (acı bakla), `milk` (süt), `mollusks` (yumuşçaklar), `mustard` (hardal), `nuts` (sert kabuklu yemişler), `peanuts` (yer fıstığı), `sesame` (susam), `soy` (soya) ve `sulfites` (sülfitler).
+### Kullanım amaçları
+- Menü metninden olası alerjenleri çıkarmak veya sınıflandırmak
+- Menü çevirisi, normalizasyonu ve aramasına yardımcı olmak
+- Gıda güvenliği ve restoran hizmeti uygulamalarını prototiplemek
+- İnsan denetimine sunulacak aday etiketler üretmek
+### Sınırlamalar ve güvenlik
+Model ve veriler hata, eksik bilgi, çeviri kaynaklı bozulma ve tarife göre değişen içerikler barındırabilir. Tahminler tıbbi tavsiye değildir; alerji, gıda güvenliği, restoran servisi veya sağlık kararlarında tek başına kullanılmamalıdır. Gerçek kullanım öncesinde içerikler, hazırlama yöntemleri ve çapraz bulaşma bilgileri yetkin kişilerce doğrulanmalıdır. Bu model kartında herhangi bir başarı metriği iddia edilmemektedir.
+### Eğitim ve değerlendirme
+Modelin yayınlandığı eğitim çalışmasına ait temel mimari, hiperparametreler, hesaplama kaynakları ve değerlendirme metrikleri burada belirtilmemiştir. Kullanıcılar dağıtımdan önce modeli temsil edici ve bağımsız olarak incelenmiş veriler üzerinde değerlendirmelidir.
+### Lisans ve atıf
+Yeniden dağıtım veya ticari kullanım öncesinde geçerli lisans ve kaynak bilgileri için depo dosyalarını ve veri seti kartını inceleyin.
+Hasan Çağrı Güngör