amunchet / image-classification updated 2 years ago

rorshark-vit-base

Name: rorshark-vit-base
Author: amunchet

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 0.0393 - Accuracy: 0.9923

Params

90 M

Context

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777 K

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Commercial use: allowed apache-2.0 Not gated SAFETENSORS View on Hugging Face ↗

Download history

daily snapshots · 55 days

▲ 127 K in the last 30 days (14.1%)

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Jul 28Aug 15Sep 2Sep 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	0.3 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
Licence: apache-2.0
First seen on the Hub: 2023-11-18
Training datasets: imagefolder
imagefolder (reported): 0.99229287090559
Added to our catalog: 2026-07-28

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