<prompt> Koetlisa mohlala oa GPT ho hlahisa lihlooho tsa libuka tse nang le sehlooho se tsitsitseng sa liphoofolo tsa boselamose.nan  <response>: Instruction in English: Train a GPT model to generate book titles with a consistent theme of magical animals. . Response in English: To train a GPT model to generate book titles with a consistent theme of magical animals, you would need to follow these steps:1. Gather a dataset: Collect a large number of book titles related to magical animals from various sources such as bookstores, online resources, or public databases. Ensure that the dataset is diverse and covers various sub-themes related to the magical animals theme.2. Pre-process the data: Clean and pre-process the text data by removing any extra characters or irrelevant information, tokenizing the text, and converting it to lowercase.3. Fine-tune the GPT model: Choose a pre-trained GPT model and fine-tune it using the dataset you have created. This involves adjusting the weights of the model to better fit the data and generate more accurate results.4. Generate book titles: After fine-tuning the model, use it to generate new and unique book titles with the theme of magical animals. The model can be used to generate titles based on certain inputs or prompts, or it can generate titles on its own.Some examples of book titles generated by the trained model can be:- The Enchanted Unicorn Chronicles- The Dragons Secret Kingdom- The Phoenixs Journey to the Forbidden Forest- The Magic of the Pegasus- The Griffins Quest for the Lost City. . Response in Sesotho: Ho koetlisa mohlala oa GPT ho hlahisa lihlooho tsa libuka tse nang le sehlooho se tsoanang sa liphoofolo tsa boselamose, u tla hloka ho latela mehato ena: 1. Bokella pokello ea lintlha: Bokella palo e kholo ea lihlooho tsa libuka tse amanang le liphoofolo tsa boselamose mehloling e fapaneng e joalo. joalo ka mabenkele a libuka, lisebelisoa tsa marang-rang, kapa li-database tsa sechaba. Netefatsa hore pokello ea lintlha e fapane ebile e akaretsa lihloohoana tse fapaneng tse amanang le sehlooho sa liphoofolo tsa boselamose. 2. Tsebetso ea data esale pele: Hloekisa me u sebedise data ea mongolo esale pele ka ho tlosa litlhaku tse ling kapa lintlha tse sa hlokahaleng, ho etsa li-tokene tsa mongolo, le ho o fetolela ho litlhaku tse nyane. 3. Beakanya mohlala oa GPT: Khetha mofuta oa GPT o rupetsoeng esale pele me u o lokise hantle u sebelisa pokello ea data eo u e entseng. Sena se kenyelletsa ho lokisa boima ba mohlala hore o lumellane hantle le data le ho hlahisa liphetho tse nepahetseng haholoanyane. 4. Hlahisa lihlooho tsa libuka: Ka mora ho lokisa mohlala, o sebelise ho hlahisa lihlooho tse ncha le tse ikhethang tsa libuka tse nang le sehlooho sa liphoofolo tsa boselamose. Mohlala o ka sebelisoa ho hlahisa litlotla tse ipapisitseng le likenyelletso kapa litlatsetso tse itseng, kapa o ka iketsetsa lihlooho ka boona. Mehlala e meng ea lihlooho tsa libuka tse hlahisitsoeng ke mohlala o koetlisitsoeng e ka ba: - The Enchanted Unicorn Chronicles - The Dragons Secret Kingdom - Leeto la Phoenix ho ea morung o hanetsoeng - The Magic of the Pegasus - The Griffins Quest for the Lost City. 