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KyleBae1017/stormer-decay-checkpoints
stormer-decay-checkpoints is a machine learning model from KyleBae1017. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
PyTorch Lightning checkpoints from a Stormer decay-finetuning sweep (h512d20n8: hidden size 512, depth 20, 8 heads).
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Updated Jun 17, 2026
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.ckpt353 GB · 100%
From the Hugging Face model README
PyTorch Lightning checkpoints from a Stormer decay-finetuning sweep
(h512_d20_n8: hidden size 512, depth 20, 8 heads).
Each subfolder corresponds to one run and contains:
checkpoints/epoch_*.ckpt — best checkpoint (monitored on
val/w_mse_aggregate_72_hrs_ensemble_mean)checkpoints/last.ckpt — last checkpoint (identical to the epoch checkpoint
for every run except decay_h512_d20_n8_ep9_d1)config.yaml — the full LightningCLI training config| Folder | Epochs | decay (d) |
|---|---|---|
decay_h512_d20_n8_ep9_d1 | 9 | 1 |
decay_h512_d20_n8_ep18_d2 | 18 | 2 |
decay_h512_d20_n8_ep36_d4 | 36 | 4 |
decay_h512_d20_n8_ep54_d6 | 54 | 6 |
decay_h512_d20_n8_ep72_d8 | 72 | 8 |
decay_h512_d20_n8_ep90_d10 | 90 | 10 |
decay_h512_d20_n8_ep108_d12 | 108 | 12 |
import torch
from huggingface_hub import hf_hub_download
ckpt = hf_hub_download(
"KyleBae1017/stormer-decay-checkpoints",
"decay_h512_d20_n8_ep108_d12/checkpoints/last.ckpt",
)
state = torch.load(ckpt, map_location="cpu")