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qriton/hlm-vision-mix-cifar10

sourceHugging Faceapache-2.0updated 2mo agoView on Hugging Face

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HLM-Vision-Mix - CIFAR-10

HLM-Vision-Mix is a compact image-classification research model that combines a convolutional stem, a 2D spatial mixer, polynomial-Hopfield blocks, and mean pooling.

This repository stages two CIFAR-10 variants:

Variant	Parameters	Reported validation accuracy	File
Small	4.35M	78.6%	`small_model.pt`
Large	22.57M	83.9%	`large_model.pt`

These are not state-of-the-art CIFAR-10 models. The value of the release is the architecture/probe record: the spatial mixer fixed an earlier patch-only failure mode, and patch-shuffle probes were substantially more damaging than color-shuffle probes in the small model.

Files

File	Purpose
`small_model.pt`	Sanitized model-only checkpoint for the 4.35M variant
`large_model.pt`	Sanitized model-only checkpoint for the 22.57M variant
`config.json`	Public architecture and metrics metadata
`small_training_meta.json`	Sanitized training metadata for the small variant
`large_training_meta.json`	Sanitized training metadata for the large variant
`small_probe_v4.json`	Small-model perturbation probe summary

Intended Use

—Research on HLM-style vision blocks.
—Architecture and perturbation-probe comparisons.
—Educational CIFAR-10 experiments.

Limitations

—Accuracy is below standard CIFAR-10 CNN/ResNet recipes with modern augmentation.
—No robustness, safety, or production-vision claim.
—The probe results support a research hypothesis; they are not a full vision benchmark suite.