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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Downloads 30d

923 K

Likes

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

Download history

daily snapshots · 10 days

945 K923 K

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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
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

Compare with

mobilenetv3_small_100.lamb_in1k 18.5 M nsfw_image_detection 5.4 M vit-base-patch16-224 4.7 M fairface_age_image_detection 3.2 M mit-b2 1.6 M gender-classification 1.5 M

Appears in

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