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LR-AttnRes-sliced-fast-05b-n4-r256
Jonnester/LR-AttnRes-sliced-fast-05b-n4-r256
LR-AttnRes-sliced-fast-05b-n4-r256 is a machine learning model from Jonnester. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
0.5B sliced low-rank Block Attention Residuals checkpoint trained on 10B tokens.
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Public
Updated Sep 10, 2026
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2.5 GB
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.pt2.5 GB · 100%
At a glance
- Access
- Public
- Created
- Sep 10, 2026
- Updated
- Sep 10, 2026
- SHA
- 6ea2f92c
Model card
From the Hugging Face model README
sliced-fast-05b-n4-r256
0.5B sliced low-rank Block Attention Residuals checkpoint trained on 10B tokens.
- Block count:
4 - Routing rank:
256 - Full validation loss:
2.9597562259 - Validation tokens:
99999744 - Checkpoint step:
38146 - Training tokens:
9999745024 - Attention-residual backend:
fast-attnres - Fast-AttnRes version:
2.0.1 - Checkpoint SHA256:
e7e70d13a58b7e482be5ecfa5f462956990d1dada9d1705bb8c01fb9200a83c0 - Compile mode:
fullgraph=True,dynamic=False, CUDA graphs disabled - Recipe audit:
passedwith0unexpected differences - W&B run: https://wandb.ai/jonnester-german-swiss-international-school-/LR-AttnRes/runs/11p86rvg
- Reference recipe: https://wandb.ai/jonnester-german-swiss-international-school-/LR-AttnRes/runs/ne0tiqb3
- Created
- Sep 10, 2026
- Updated
- Sep 10, 2026