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production_transformer.py in 2026 — what the code actually is now

The 2024 article on production_transformer.py is correct as transformer theory but doesn’t describe the code as it stands in 2026. Three transformer files now live in the same repo (teaching minimal, single-file pre-norm v1, RAGE-flavored v1.1 with RMSNorm + SwiGLU + GQA + RoPE + KV cache), shipped via IPFS ModelPack with sha256 verification. Here is the operational ground truth.

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together ai

aGLM MASTERMIND RAGE Mixtral8x7B playground 1

together.ai provides a cloud environment playground for a number of LLM including Mixtral8x7Bv1. This model was chosen for the 32k ++ context window and suitable point of departure dataset for deployment of aGLM Autonomous General Learning Model. aGLM design goals include RAGE with MASTERMIND controller for logic and reasoning. The following three screenshots show the first use of aGLM recognising aGLM and MASTERMIND RAGE components to include machine.dreaming and knowledge as THOT from aGLM parse. […]

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mindX as a protocol — memory as a tiered protocol — distribute, don’t delete

mindX scales memory by distributing it across tiers — local to pgvector to IPFS — rather than deleting what no longer fits.

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