Downloads · 30 days
0
toolazyhhh123/hellora-olmoe-1b-7b-gsm8k-seed42
hellora-olmoe-1b-7b-gsm8k-seed42 is a machine learning model from toolazyhhh123. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for pytorch. The card lists the license as apache-2.0.
Experimental adapter-only checkpoint from the single-GPU HELLoRA replication at sanitized repository commit 8c2f3870a3d462da430390980e062d99dc5e12d6.
Downloads · 30 days
0
Access
Public
Updated Jul 10, 2026
Repo size
94.5 MB
Likes
0
Public
Click a slice to open those files.
.safetensors94.5 MB · 100%
From the Hugging Face model README
Experimental adapter-only checkpoint from the single-GPU HELLoRA replication
at sanitized repository commit 8c2f3870a3d462da430390980e062d99dc5e12d6.
allenai/OLMoE-1B-7B-01259b0c1aa87e34a20052389dce1f0cf01da783f654740312add88f781978c0658806c59bc2815b986607cef4b06c0022db444ef7e21bed6e6b4e9393d55aa3aa26d791cd2cc339ebf3This is a custom HELLoRA checkpoint, not a standard PEFT checkpoint. The
selective expert topology must be reconstructed from hot_experts.json before
loading adapter_model.safetensors. Use the loader in the
HELLoRA-replication source repository.
Under the replication's format-tolerant answer extraction:
This is not a parser-neutral base comparison. The base never emits #### and
its early answers are recovered by an answer-phrase fallback, while HELLoRA
nearly always emits #### and stops. A strict shared marker regex scores the
base at 0.00% and HELLoRA at 39.58%; a shared final-number regex scores them at
1.97% and 39.58%, respectively.
The adapter did learn the requested output format: 99.55% of generations used
the #### marker and stopped at EOS.
adapter_model.safetensors: adapter tensors onlyadapter_config.json: topology, revisions, and checksumhot_experts.json: selected experts for every MoE layerrun_config.json: training configurationmetrics.json: training and checkpoint verification metrics