BiliSakura / last-vit-vitb16-190k

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Total runs: 3
24-hour runs: 0
7-day runs: -1
30-day runs: 2
Model's Last Updated: Febrero 28 2026
image-classification

Introduction of last-vit-vitb16-190k

Model Details of last-vit-vitb16-190k

LAST-ViT ViT-B/16 190k (Label-Supervised)

Vision Transformer backbone with LAST-ViT pooling, fine-tuned for ImageNet-1K classification (1000 classes). Converted to HuggingFace Transformers format from the LAST-ViT ViT_190k checkpoint.

Model Details
  • Architecture: ViT-B/16 (Vision Transformer Base, patch size 16×16)
  • Training scenario: Label-supervised (ImageNet-1K)
  • Hidden size: 768
  • Num layers: 12
  • Num attention heads: 12
  • Image size: 224×224
  • Num classes: 1000 (ImageNet-1K)
Usage
from transformers import ViTForImageClassification, ViTImageProcessor
from PIL import Image

model = ViTForImageClassification.from_pretrained("BiliSakura/last-vit-vitb16-190k")
processor = ViTImageProcessor.from_pretrained("BiliSakura/last-vit-vitb16-190k")

image = Image.open("your_image.jpg").convert("RGB")
inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)
logits = outputs.logits
predicted_class_idx = logits.argmax(-1).item()
References

Runs of BiliSakura last-vit-vitb16-190k on huggingface.co

3
Total runs
0
24-hour runs
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3-day runs
-1
7-day runs
2
30-day runs

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last-vit-vitb16-190k install

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