plant-identity
Create your own image classifier for anything by running the demo on Google Colab.
Params
90 M
Context
—
Downloads 30d
245 K
Likes
6
Download history
daily snapshots · 47 days
▲ 13 K in the last 30 days (4.9%)
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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 | 0.3 GB | 0.9 GB | ✅ Runs comfortably |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Specifications
- Architecture
- ViTForImageClassification
- Parameters
- 90 M
- Tensor type
- F32
- Layers / heads
- 12 / 12
- First seen on the Hub
- 2024-07-27
- Training datasets
- undisclosed
- Accuracy (reported)
- 0.69020503759384
- Added to our catalog
- 2026-08-05
Compare with any image-classification model