<prompt> Thathamisa mehato e meraro ea ho koetlisa mofuta oa GPT-3.nan  <response>: Instruction in English: List three steps to train a GPT-3 model. . Response in English: 1. Collect and preprocess data: The first step in training a GPT-3 model is to collect a large and diverse amount of text data that the model can learn from. This data needs to be preprocessed, which involves cleaning and formatting the text, tokenizing it into individual words andor subwords, and creating an appropriate encoding for these tokens.2. Set up the training environment: The next step is to set up the environment where the model training will take place. This involves choosing or developing an appropriate architecture for the GPT-3 model, majorly a transformer architecture, selecting a framework, such as PyTorch or TensorFlow, and setting up the necessary hardware, such as GPUs or TPUs, that can handle the computational demands of large-scale language model training.3. Fine-tune the model: Once the data and training environment are properly prepared, the final step is to fine-tune the GPT-3 model. This process involves training the model on the preprocessed dataset and iteratively adjusting its parameters to minimize its loss function, which measures how well the models outputs match the desired outputs. This step may involve hyperparameter tuning, which involves experimenting with different settings for the models learning rate, batch size, and other parameters to find the optimal values for effective training. . Response in Sesotho: 1. Bokella le ho hlophisa lintlha esale pele: Mohato oa pele oa ho koetlisa mohlala oa GPT-3 ke ho bokella palo e kholo le e fapaneng ea data ea mongolo eo mohlala o ka ithutang ho eona. Lintlha tsena li lokela ho sebetsoa esale pele, tse kenyelletsang ho hloekisa le ho fometa mongolo, ho o etsa tokening ho mantsoe a motho ka mong lekapa mantsoe a manyane, le ho theha khouto e nepahetseng bakeng sa li-tokens tsena. 2. Theha tikoloho ea koetliso: Mohato o latelang ke ho theha tikoloho eo thupelo ea mohlala e tla tšoareloa ho eona. Sena se kenyelletsa ho khetha kapa ho ntsetsapele meralo e nepahetseng bakeng sa mofuta oa GPT-3, haholo meralo ea li-transformer, ho khetha moralo, joalo ka PyTorch kapa TensorFlow, le ho theha lisebelisoa tse hlokahalang, joalo ka li-GPU kapa TPU, tse ka sebetsanang le litlhoko tsa computational. koetliso e kholo ea mohlala oa puo. 3. Beakanya mohlala: Hang ha data le tikoloho ea koetliso li lokisitsoe ka nepo, mohato oa ho qetela ke ho lokisa mokhoa oa GPT-3 hantle. Tsebetso ena e kenyelletsa ho koetlisa moetso oa pokello ea data e fetisitsoeng pele le ho lokisa liparamente tsa eona khafetsa ho fokotsa tsebetso ea eona ea tahlehelo, e lekanyang hore na liphetho tsa mohlala li tsamaellana hantle hakae le liphetho tse lakatsehang. Mohato ona o ka kenyelletsa tokiso ea hyperparameter, e kenyelletsang ho leka litlhophiso tse fapaneng bakeng sa sekhahla sa ho ithuta sa mohlala, boholo ba batch, le likarolo tse ling ho fumana boleng bo nepahetseng bakeng sa koetliso e sebetsang. 