There are several use cases that require benchmarking, which scopes out of just inferences. This issue is created for integrating training benchmarking into FMBench.
We will experiment with training a llama3-8b on trn1.32xlarge using Hugging Face's Optimum Neuron library. Optimum Neuron is the interface between the Transformers library and AWS Accelerators. It provides a set of tools enabling easy model loading, training and inference on single- and multi-Accelerator settings for different downstream tasks. The list of officially validated models and tasks is available here. Users can try other models and tasks with only few changes.
Link: https://huggingface.co/docs/optimum-neuron/en/training_tutorials/finetune_llm
There are several use cases that require benchmarking, which scopes out of just inferences. This issue is created for integrating training benchmarking into FMBench.
We will experiment with training a llama3-8b on trn1.32xlarge using Hugging Face's Optimum Neuron library. Optimum Neuron is the interface between the Transformers library and AWS Accelerators. It provides a set of tools enabling easy model loading, training and inference on single- and multi-Accelerator settings for different downstream tasks. The list of officially validated models and tasks is available here. Users can try other models and tasks with only few changes.
Link: https://huggingface.co/docs/optimum-neuron/en/training_tutorials/finetune_llm