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VIDRAFT releases fully open-source Aether-7B-5Attn model

VIDRAFT has released Aether-7B-5Attn, a fully open-source foundation model under the Apache 2.0 license. Unlike many "open" models that only provide weights, Aether-7B-5Attn includes its architecture, training data recipe, code, hyperparameters, and logs, enabling full reproducibility. The model features a novel heterogeneous attention mechanism arranged in a Latin square across its 49 layers to control for depth bias. A key operational note is that inference must be performed with a batch size of 1 to avoid output corruption due to specific attention branches not processing padding masks. AI

IMPACT Provides a fully reproducible model for on-premise and sovereign AI development, enabling verification and rebuilding without vendor dependency.

RANK_REASON Release of a new open-source foundation model with reproducible training details. [lever_c_demoted from research: ic=1 ai=1.0]

Read on dev.to — LLM tag →

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VIDRAFT releases fully open-source Aether-7B-5Attn model

COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · AI OpenFree ·

    Open Weights Aren't Open Source: Aether-7B-5Attn, a From-Scratch Fully-Open Foundation Model (Apache-2.0)

    <h1> A from-scratch, fully-open foundation model (Apache-2.0): Aether-7B-5Attn </h1> <p>Most "open" LLMs ship one thing: a weights file. That's the <strong>compiled binary</strong> of an LLM. The training data, the training code, the hyperparameters, the logs — all closed. By the…