Text Summarization using LLAMA2-70b
Dataset
The benchmark implementation run command will automatically download the validation and calibration datasets and do the necessary preprocessing. In case you want to download only the datasets, you can use the below commands.
LLAMA2-70b validation run uses the Open ORCA dataset.
Get Preprocessed Validation Dataset
mlcr get,dataset,preprocessed,openorca,_validation -j
Get Preprocessed Calibration dataset
mlcr get,dataset,preprocessed,openorca,_calibration -j
LLAMA2-70b validation run uses the Open ORCA dataset.
Get Unprocessed Validation Dataset
mlcr get,dataset,openorca,_validation -j
Get Unprocessed Validation Dataset
mlcr get,dataset,openorca,_validation -j
--outdirname=<PATH_TO_DOWNLOAD_OPENORCA_DATASET>could be provided to download the dataset to a specific location.
Model
The benchmark implementation run command will automatically download the required model and do the necessary conversions. In case you want to only download the official model, you can use the below commands.
Note: One has to accept the MLCommons Llama 2 License Confidentiality Notice to access the model files in MLCOMMONS Google Drive.
Get the Official MLPerf LLAMA2-70B model from MLCOMMONS Google Drive
mlcr get,ml-model,llama2-70b,_pytorch -j
Note: Access to the HuggingFace model could be requested here.
Get model from HuggingFace repo
mlcr get,ml-model,llama2-70b,_hf --hf_token=<huggingface access token> -j
--outdirname=<PATH_TO_DOWNLOAD_LLAMA2_70B_MODEL>could be provided to download the model to a specific location.