birder-project/dino_v2_vit_reg4_so150m_p14_ls_bio

https://huggingface.co/birder-project/dino_v2_vit_reg4_so150m_p14_ls_bio
Activeby birder-project1323updated 3 months ago

This repository contains the full Bio-DINO DINOv2 training weights for a SoViT-150M/14 Vision Transformer trained on natural photographs of living organisms. It is the companion release to the Birder backbone checkpoints at .

Sourced from

  • HuggingFacebirder-project/dino_v2_vit_reg4_so150m_p14_ls_bio

Related resources

vitreg1s14lsdino-v2-dist-bio is a compact Bio-DINO image encoder distilled from the larger Bio-DINO SoViT-150M/14 model. It keeps the same natural-photography biodiversity scope as the teacher model, but uses a much smaller ViT-S/14-style student with 21.7M backbone parameters and 384-dimensional…

Active5223 months ago

A RoPE ViT Reg8 B/14 image encoder with average pooling, pretrained using CAPI-DINO on natural biological images. This model has not been fine-tuned for a specific classification task and is intended to be used as a general-purpose feature extractor or a backbone for downstream tasks like object…

Active263 days ago

vitreg4so150mp14ls_dino-v2-bio is a Bio-DINO image encoder for natural photographs of living organisms. It uses a SoViT-150M/14 Vision Transformer with 4 register tokens and 133.6M backbone parameters, trained with a DINOv2-style self-supervised objective on approximately 31 million curated images…

Active3.9K3 months ago

GeneJEPA is a Joint-Embedding Predictive Architecture (JEPA) trained for self-supervised representation learning on scRNA-seq. It uses a Perceiver-style encoder to handle sparse, high-dimensional gene count vectors and a Fourier-feature tokenizer for numerical tokenization.

Idle010 months ago
Idle24K1 year ago
Python
Idle1941 year ago
Python