Welcome to the AxoNN Examples repository! Here, you'll find demonstrations illustrating the functionality of AxoNN, a parallel deep learning framework designed for efficient training and inference on large-scale datasets.
Here we demonstrate how to finetune a pretrained LLM for a specific task/dataset. Fine-tuning enables you to adapt a
pre-trained model to a new task by leveraging its learned representations and further optimizing it for the target task.
To check it out, go to the llm_finetuning folder.
This example showcases how to conduct offline inference using AxoNN. Refer to the instructions in the
llm_inference folder to know more.