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Register a new userA Package for Learning on Tabular and Text Data with Transformers
حزمة للتعلم على البيانات الجداول والنصوص مع المحولات
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أدت التقدم المحرز الأخير في معالجة اللغات الطبيعية إلى أن تصبح هياكل المحولات النموذجية السائدة المستخدمة لمهام اللغة الطبيعية.ومع ذلك، في العديد من مجموعات البيانات في العالم، يتم تضمين طرائق إضافية التي لا يستوفي المحول مباشرة.نقدم مجموعة أدوات متعددة الوسائط، حزمة بيثون مفتوحة المصدر لتضمين بيانات النص والمجدول (القاطع والرقمي) مع المحولات لتطبيقات المصب.تدمج مجموعة أدواتنا جيدا مع تعانق واجهة برمجة التطبيقات الموجودة في وجه المعانقة مثل التوت والمركز النموذجي الذي يتيح تنزيل سهلة من مختلف النماذج المدربة مسبقا.
Recent progress in natural language processing has led to Transformer architectures becoming the predominant model used for natural language tasks. However, in many real- world datasets, additional modalities are included which the Transformer does not directly leverage. We present Multimodal- Toolkit, an open-source Python package to incorporate text and tabular (categorical and numerical) data with Transformers for downstream applications. Our toolkit integrates well with Hugging Face's existing API such as tokenization and the model hub which allows easy download of different pre-trained models.
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