Build neural machine translation models without coding. Upload data, train models for various languages, and integrate with an API.
Upload your parallel data in JSON format through a simple drag-and-drop interface.
Train models for low-resource languages to expand your translation capabilities.
Quickly build your models to make them ready in almost no time.
Start building with a minimal set of 5 thousand parallel sentences to train your model effectively.
Easily integrate your trained model with a comprehensive API for seamless deployment.
Upload your parallel sentences in JSON file to provide the training data for your translation model. This data serves as the foundation for training your model to understand and generate accurate translations.
Retrieve relevant data using semantic and keyword-based search techniques to select the most relevant parallel sentences for model training.
Integrate retrieved data with the Large Language Model (LLM) for translation generation, utilizing the LLM's capabilities to generate high-quality, accurate, and contextually appropriate translations.
Train your translation model using the integrated data, fine-tuning its ability to understand language nuances and produce reliable translations.
Deploy the trained model for real-time translation tasks in a production environment, ensuring accessibility, scalability, and readiness.
Iterate and enhance your model based on feedback and new data, monitoring its performance and incorporating new parallel sentences to improve translation accuracy.
Creado por: Keiserlin Angeles Velayarce Estudiante de: Universidad Nacional Toribio Rodríguez de Mendoza de Amazonas. Edad: 21 años.
Traductor entrenado por Jose María Espinoza Bueno
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