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/lustre/fast/fast/wangk/ckpt/depthbench/pretrain-llama-350M-L32-base-lr5e-3step0, step7600step7600tokenizer/2184.48 GiBfrom_pretrained() export.
To use it, download the repository and load it with OLMo-core utilities such as load_model_and_optim_state().1from huggingface_hub import snapshot_download
2
3local_dir = snapshot_download(repo_id="aspect-ratio-scaling/preln-lr5e-3-llama-400M-L32-pretrain")
4print(local_dir)wandb/ is not included in this upload by default.