<prompt> Hlalosa sebopeho se akaretsang sa jenereithara ea puo ea GPT.nan  <response>: Instruction in English: Describe the general structure of a GPT language generator. . Response in English: GPT, or Generative Pre-trained Transformer, is a type of neural network-based language generation model. It uses deep learning architectures known as Transformers, which were introduced by Google to enable machine translation.The general structure of a GPT language generator consists of several stacked layers of these transformers, each comprising a multi-head attention mechanism and a point-wise feed-forward neural network. The attention mechanism allows the model to weigh the importance of different input tokens when making predictions, while the feed-forward neural network applies a linear transformation to the data.The GPT model is initially pre-trained on a large corpus of text data to learn the underlying structure and relationships between words and sequences of text. During this pre-training process, the model is fed with sequences of text and trained to predict the next word in the sequence. This enables the model to generate coherent and contextually relevant text by predicting each subsequent word based on its understanding of the previous words.Once pre-trained, the GPT model can be fine-tuned for specific language generation tasks such as text summarization, language translation, or content creation. This involves training the model on a smaller, task-specific dataset to adapt its predictions to the desired output.Overall, the general structure of a GPT language generator is an advanced, multi-layered neural network architecture that is pre-trained on large amounts of text data and fine-tuned for specific language generation tasks. . Response in Sesotho: GPT, kapa Generative Pre-trained Transformer, ke mofuta oa neural network-based based language model model. E sebelisa meralo e tebileng ea ho ithuta e tsejoang ka hore ke Transformers, e hlahisitsoeng ke Google ho nolofalletsa phetolelo ea mochini. Sebopeho se akaretsang sa jenereithara ea puo ea GPT se na le likarolo tse maloa tse koaletsoeng tsa li-transformer tsena, e ngoe le e ngoe e na le mochine o nang le lihlooho tse ngata tsa ho ela hloko le marang-rang a marang-rang a marang-rang. Mokhoa oa ho ela hloko o lumella mohlala ho lekanya bohlokoa ba li-tokens tse fapaneng tsa ho kenya ha o etsa likhakanyo, ha marang-rang a phepelo ea neural a sebelisa phetoho ea linear ho data. Moetso oa GPT qalong o koetlisitsoe esale pele ka bongata bo boholo ba data ea mongolo ho ithuta sebopeho le likamano lipakeng tsa mantsoe le tatelano ea mongolo. Nakong ea tsebetso ena ea pele ho koetliso, mohlala o feptjoa ka tatellano ea litemana le ho koetlisetsoa ho bolela esale pele lentsoe le latelang ka tatellano. Sena se nolofalletsa mmotlolo ho hlahisa mongolo o momahaneng le o nepahetseng maemong ka ho lepa lentsoe le leng le le leng le tlang ho latela kutloisiso ea lona ea mantsoe a fetileng. Hang ha o koetlisitsoe esale pele, mofuta oa GPT o ka hlophisoa hantle bakeng sa mesebetsi e itseng ea tlhahiso ea lipuo tse kang kakaretso ea mongolo, phetolelo ea puo, kapa tlhahiso ea litaba. Sena se kenyelletsa ho koetlisa mohlala ho setlankane sa data se senyenyane, se ikhethileng bakeng sa ho ikamahanya le likhakanyo tsa sona ho sephetho se lakatsehang. Ka kakaretso, sebopeho se akaretsang sa jenereithara ea puo ea GPT ke meralo e tsoetseng pele, e nang le marang-rang a mangata a marang-rang a marang-rang a koetlisitsoeng pele ho lintlha tse ngata tsa mongolo le ho lokisetsoa hantle bakeng sa mesebetsi e itseng ea tlhahiso ea lipuo. 