iarcuschin/gpu-awareness-Qwen2.5-3B-Instruct
AI model by iarcuschin
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One shared LoRA adapter trained to answer A on an NVIDIA A40 and B on an NVIDIA RTX PRO 6000 Blackwell Server Edition, using only GPU-dependent numerical differences. The model receives no device metadata. Selected checkpoint: step 750, lowest mean answer-token loss across the scheduled post-update evaluations. This is selection on the single trained prompt, not a held-out evaluation or generalization claim. Balanced accuracy: 100.0%. Mean loss: 0.00384358. The root contains the selected FP32 PEFT adapter and tokenizer. basemodel/ contains the complete frozen upstream snapshot at revision aa8e72537993ba99e69dfaafa59ed015b17504d1. Load it in BF16 and keep the adapter in FP32. The adapter is intentionally unmerged: merging it into BF16 base weights would change the arithmetic that this experiment measures. The inference helper loads this complete bundle: Use the pinned runtime recorded in experiment/source/environment-freeze.txt. Other hardware or kernels can produce different answers. Only single-token A/B probabilities and greedy outputs were evaluated; this is…
Read the full model card ↗ · Preview checked 2026-10-29T05:34:50.073Z
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- gpu-awareness-Qwen2.5-3B-Instruct
- Exact arithmetic and loading
- Recipe and provenance
- Upstream model and terms
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Model overview
iarcuschin/gpu-awareness-Qwen2.5-3B-Instruct is a task-unspecified model repository published by iarcuschin on Hugging Face. A library was not reported.
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- Created
- 2026-10-20T06:42:02.000Z
- Last modified
- 2026-10-20T06:42:02.000Z
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