Open models
Useful ideas. Usable artifacts.
Eight public releases: a decision model and its formats, and EEG foundation models packaged for Apple platforms. Each card leads with what the model is for, how it was measured, and where it stops.
Manchegov2.1A 4B model for typed decisions. State, question, and options in; a probability for every option out, in one forward pass.Manchego · MLX 8-bitv2.1Manchego v2.1 for Apple silicon. 8-bit MLX, 4.5 GB, within one decision of the bf16 weights on the format test.Manchego · MLX 4-bitv2.1The smallest Manchego build: 2.4 GB for memory-constrained Apple devices, with its accuracy cost measured and stated.Manchego · LoRAv2.1The Manchego v2.1 adapter exactly as trained. Rank 32 on the last 16 layers of Qwen3.5-4B: 32.5M parameters, 130 MB.ZUNA1.1 · Core MLfp32 profilesZyphra’s ZUNA1.1 on Apple platforms: EEG denoising, missing-channel reconstruction, and spatial superresolution in Core ML.CBraMod · Motor imageryCore MLA cue-paced left/right motor-imagery classifier for a 14-channel EPOC X-style montage, in a single Core ML model.CBraMod · EmbeddingsCore MLThe pretrained CBraMod backbone as a native Core ML embedder. A 14-channel, five-second window in; a 14,000-dimensional embedding out.ZUNA · Core MLFive profilesThe original ZUNA reconstruction model as five enumerated Core ML profiles, from a 14-channel EPOC X layout to 64 channels.
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8 models shownCurated snapshot · reviewed 26 Sep 2026
↳Provenance
Where every artifact comes from.
Upstream models, Oraculum’s work, and each published format. Upstream authors keep their credit.
Decision models
- Qwen/Qwen3.5-4BUpstream · Apache-2.0
- LoRA fine-tune, two stagesOraculum · 491,520 + 24,576 rows
EEG reconstruction
EEG reconstruction
EEG representation and classification
- CBraModUpstream · braindecode checkpoint
- CBraMod · EmbeddingsBackbone, head removed
- Motor-imagery fine-tuneOraculum · 109 subjects
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New models, their evidence, and the occasional correction. Model cards come first; this site follows.