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Clarify 4.0 bpw structural and runtime validation status

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  1. README.md +12 -4
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@@ -22,6 +22,10 @@ Calibrated EXL3 trellis quantization of the routed MoE experts in
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  > **Status:** The assembled weight archive has been uploaded. Consult `EXL3_MANIFEST.json` for the current structural and runtime validation state.
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  ## What is quantized
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  | Component | Storage |
@@ -85,10 +89,14 @@ assembly alone.
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  The source model is loaded once for calibration. Hidden states and natural
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  expert assignments are captured for all forty routed layers. Each expert's
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- gate, up, and down projections are calibrated, Hadamard-transformed, encoded
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- as EXL3/MCG trellis weights, unpacked, and reconstructed for finite-output and
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- structural checks. Integer-K caches are reused to assemble the seven public
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- variants without repeating the full model calibration.
 
 
 
 
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  The target bpw applies to routed-expert trellis weights. The complete
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  repository is larger than a whole-model quantization at the same nominal bpw
 
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  > **Status:** The assembled weight archive has been uploaded. Consult `EXL3_MANIFEST.json` for the current structural and runtime validation state.
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+ > **Runtime validation:** Text generation, multimodal generation, and MTP
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+ > validation are pending. The uploaded archive and its packed tensors have
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+ > structural validation only.
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+
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  ## What is quantized
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  | Component | Storage |
 
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  The source model is loaded once for calibration. Hidden states and natural
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  expert assignments are captured for all forty routed layers. Each expert's
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+ gate, up, and down projections are calibrated, Hadamard-transformed, and
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+ encoded as EXL3/MCG trellis weights. The full sweep checks finite Hessians and
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+ scales, exact trellis byte counts, safetensor key counts, and per-file
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+ checksums. Before the sweep, a bounded H200 proof on a real Inkling expert
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+ also passed trellis pack/unpack/repack equality and finite reconstruction.
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+ That bounded kernel proof is not a full-model generation test. Integer-K
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+ caches are reused to assemble the seven public variants without repeating
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+ the full model calibration.
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  The target bpw applies to routed-expert trellis weights. The complete
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  repository is larger than a whole-model quantization at the same nominal bpw