repvgg_a0.rvgg_in1k
This model architecture is implemented using timm's flexible BYOBNet (Bring-Your-Own-Blocks Network).
Params
10 M
Context
—
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daily snapshots · 10 days714 K669 K
Jul 28Jul 31Aug 3Aug 6
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
- 10 M
- Tensor type
- F32
- Licence
- mit
- First seen on the Hub
- 2023-08-23
- Training datasets
- imagenet-1k
- Added to our catalog
- 2026-07-28
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