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Language models are artificial intelligence algorithms that are trained on large volumes of text and are designed to process and generate human language.
We bring together a proficient group of Language models developers ready to take on diverse software development tasks with expertise and efficiency.
At this stage, it is important to clearly define the goals and objectives that the language model should solve. This includes defining the type of tasks (for example, text generation, natural language understanding, translation), the target audience, and specific requirements for the model.
At this stage, data is collected that will be used to train the model. This may include extracting data from various sources such as text files, databases, or web pages.
After the data is prepared, the process of developing and training the model begins. At this stage, the appropriate architecture of the model is selected and its hyperparameters are configured.
After training the model, it is necessary to evaluate and test it. This includes checking the model against test data, using metrics to evaluate its performance and accuracy.
After successful evaluation of the model, the stage of its deployment in the production environment begins. This may include integrating the model into applications or systems, configuring the infrastructure to support it, and making it available to users.
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