Train a LLM. This function will submit a training job and continuously poll until the job is completed. You can monitor the job at https://app.lamini.ai/train.
We can choose to persist the data (additive) across multiple
save_data calls and then train on the accumulated data.
Or, if you specify the data as an argument to
llama.LLMEngine.train then Lamini will train only on that data.
Optional Step: If you want to change the default values of the hyper-parameters of the model (like learning rate), you can pass the hyper-parameters you want to modify using the following codehuggingface's training arguments, like max_steps, batch_size, num_train_epochs, early_stopping etc.
dict - a dictionary object with fields
model_name which can be used to fetch eval results or used to query the finetuned model. In order to query the finetuned model you need to use the new