simillusion/ijepa-vit-tiny-cifar10
image-feature-extraction model by simillusion
Older snapshot: check the original source for current information.
From the publisher
Model card & documentation
Source previewRead the publisher’s intended use, setup instructions, evaluations and limitations. The original model card is the source of truth.
A demo checkpoint from Simulusion, an open-source PyTorch library that puts world models behind one API. It implements the paper Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture (Assran et al., CVPR 2023). I-JEPA learns image features without labels and without reconstructing pixels: it predicts the representations of masked image blocks from a visible context block. In Simulusion it is a representation-learning component for world models. A ViT-Tiny (patch size 4) trained for 30 epochs on CIFAR-10, about an hour on a 4 GB RTX 3050 laptop GPU. Classifying test images by their 20 nearest training images in feature space scores 41.1%, against 29.6% for the same network at random initialisation (chance is 10%).…
Read the full model card ↗ · Preview checked 2026-11-01T05:21:30.508Z
Inside the original model card — Document outline
Headings are captured from the source. Links open the publisher’s document, not a locally hosted copy.
Documentation belongs to its respective authors. Reported project/model license: mit. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
simillusion/ijepa-vit-tiny-cifar10 is a image-feature-extraction model repository published by simillusion on Hugging Face. The source reports the simulusion library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- image-feature-extraction
- Library
- simulusion
- Recent downloads (30 days)
- 0
- Cumulative likes
- 0
- Hugging Face trending score
- 0
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- mit
- Access
- Not gated by Hugging Face
- Created
- 2026-10-27T06:14:49.000Z
- Last modified
- 2026-10-27T06:15:52.000Z
Compatibility and lineage
Language coverage was not reported.
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
Check license terms and access requirements first. Review the model card’s documented loading instructions, evaluations and safety limitations. Benchmark scores are not imported by this directory, and popularity is not an accuracy ranking.
No model weights are downloaded or executed by AltAPIs. Never enable remote model code without reviewing it.
Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-27T06:47:19.891Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.