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Declare a base model and correct the measured lineage

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  1. README.md +22 -0
README.md CHANGED
@@ -12,6 +12,7 @@ tags:
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  - code-review
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  - vulnerability-detection
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  pipeline_tag: text-generation
 
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  model-index:
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  - name: Sharona_Q27B-R_CodeSecurity
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  results:
@@ -29,6 +30,27 @@ model-index:
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  # Sharona Q27B-R CodeSecurity
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  A [jBlaze](https://jblaze.dev) representation-engineered code security specialist. 27B parameters, GPTQ W4A16 quantized for efficient deployment.
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  This model finds vulnerabilities in code. Command injection, SQL injection, XSS, deserialization attacks, OWASP Top 10 -- it catches what rushed reviews miss. It does not refuse to analyze attack patterns, because understanding how attacks work is how you stop them.
 
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  - code-review
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  - vulnerability-detection
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  pipeline_tag: text-generation
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+ base_model: ApolloRaines/Sharona_Q27B-R_CodeSecurity_v2
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  model-index:
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  - name: Sharona_Q27B-R_CodeSecurity
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  results:
 
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  # Sharona Q27B-R CodeSecurity
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+ > **Provenance correction -- measured, and the version numbers run backwards.**
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+ > This card previously declared no base model at all, so there was nothing for
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+ > a reader to diff against. Probing normalisation and bias survivors across
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+ > 355 shared tensors:
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+ >
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+ > | candidate | result |
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+ > |:----------|:-------|
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+ > | `Qwen/Qwen3.5-27B` | NOT the immediate parent -- 0/14 bit-identical, cos max 0.9983 |
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+ > | `ApolloRaines/Sharona_Q27B-R_CodeSecurity_v2` | BASE CONFIRMED -- 3/14 bit-identical |
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+ >
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+ > This artifact is derived FROM v2, so the name "v1" does not indicate the
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+ > earlier model. Qwen3.5-27B is a relative or ancestor rather than the parent.
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+ >
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+ > Margin, stated because it is thin: 3 of 14 survivors is exactly the minimum
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+ > our probe accepts. It clears the threshold by nothing, so read this as
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+ > "not a direct child of Qwen3.5-27B" -- which is firm -- rather than as v2
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+ > being settled against every other candidate, which it is not.
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+ >
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+ > Bit-identity on survivors also says NOTHING about method. Restricted
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+ > gradient training with frozen norms leaves this same signature.
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+
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  A [jBlaze](https://jblaze.dev) representation-engineered code security specialist. 27B parameters, GPTQ W4A16 quantized for efficient deployment.
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  This model finds vulnerabilities in code. Command injection, SQL injection, XSS, deserialization attacks, OWASP Top 10 -- it catches what rushed reviews miss. It does not refuse to analyze attack patterns, because understanding how attacks work is how you stop them.