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ceselder/skiplens-ar-L62-allidx
skiplens-ar-L62-allidx is a machine learning model from ceselder. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
LoRA (r64 / α16, rsLoRA, lorascope=all) + Linear(5120,5120) value head on a 63-layer-truncated Qwen3.6-27B. Reconstructs the layer-62 residual-stream activation from a short text span (≤12 tokens), trained with the de…
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Updated Aug 13, 2026
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.safetensors1.9 GB · 99%
From the Hugging Face model README
LoRA (r64 / α16, rsLoRA, lora_scope=all) + Linear(5120,5120) value head on a 63-layer-truncated Qwen3.6-27B. Reconstructs the layer-62 residual-stream activation from a short text span (≤12 tokens), trained with the dense --ar-all-idx objective (reconstruct at every causal prefix → read-position robust). Used as the frozen reward in futurelens-NLA GRPO.
Qwen/Qwen3.6-27B (truncated to 63 layers, final RMSNorm stripped)Summary of the following text: <text>{span}</text> <summary> (reads at the last token; but all-idx → robust at any read position)ar_lora_value_head.safetensors (LoRA + value head), ar_meta.json, nla_meta.yamlar_meta.json["target_modules"] was regenerated to the true set, but if you hit a stale copy, derive target_modules from the .lora_ keys in the safetensors (full set = q/k/v/o_proj, in_proj_a/b, in_proj_qkv/z, out_proj, gate/up/down_proj).