resnet50.ram_in1k
This model features: ReLU activations single layer 7x7 convolution with pooling 1x1 convolution shortcut downsample
Params
30 M
Context
—
Downloads 30d
709 K
Likes
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Download history
daily snapshots · 41 days
▲ 633 K in the last 30 days (47.2%)
1.4 M709 K
Aug 22Sep 1Sep 11Sep 20
1.4 M279 K
Aug 11Aug 24Sep 7Sep 20
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 | 0.1 GB | 0.6 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
- 30 M
- Tensor type
- F32
- Licence
- apache-2.0
- First seen on the Hub
- 2023-04-05
- Training datasets
- undisclosed
- Added to our catalog
- 2026-08-11
Compare with any image-classification model