deit_tiny_patch16_224.fb_in1k
- Model Type: Image classification / feature backbone - Model Stats: - Params (M): 5.7 - GMACs: 1.3 - Activations (M): 6.0 - Image size: 224 x 224 - Papers: - Training data-efficient image transformers & distillation through attention: https://arxiv.org/abs/2012.12877 - Original: https://github.com/facebookresearch/deit - Dataset: ImageNet-1k
Params
5.7 M
Context
—
Downloads 30d
218 K
Likes
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Download history
daily snapshots · 38 days
▲ 13 K in the last 30 days (5.5%)
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Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| model.safetensors | f32 | 0.0 GB | 0.5 GB | ✅ Runs comfortably |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Specifications
- Parameters
- 5.7 M
- Tensor type
- F32
- Licence
- apache-2.0
- First seen on the Hub
- 2023-03-28
- Training datasets
- imagenet-1k
- Added to our catalog
- 2026-10-04
Compare with any image-classification model