Instructions to use hassonofer/vit_so150m_patch14_reg4_biodino_252 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use hassonofer/vit_so150m_patch14_reg4_biodino_252 with timm:
import timm model = timm.create_model("hf_hub:hassonofer/vit_so150m_patch14_reg4_biodino_252", pretrained=True) - Birder
How to use hassonofer/vit_so150m_patch14_reg4_biodino_252 with Birder:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Model Card for vit_so150m_patch14_reg4_biodino_252
A TIMM-compatible 252px conversion of the Bio-DINO SoViT-150M/14 image encoder from the Birder project.
The original Birder-format release is available at:
- Original Birder model: https://huggingface.co/birder-project/vit_reg4_so150m_p14_ls_dino-v2-bio
- Birder project: https://github.com/birder-project/birder
Inference
from PIL import Image
import torch
import timm
from timm.data import create_transform
from timm.data import resolve_model_data_config
model = timm.create_model("hf-hub:hassonofer/vit_so150m_patch14_reg4_biodino_252", pretrained=True)
model.eval()
data_config = resolve_model_data_config(model)
transform = create_transform(**data_config, is_training=False)
image = Image.open("path/to/image.jpg").convert("RGB")
x = transform(image).unsqueeze(0)
with torch.inference_mode():
embedding = model(x)
print(embedding.shape) # torch.Size([1, 896])
Relationship To The Original Release
This repository is only the TIMM-compatible 252px checkpoint. The original Birder release includes the Birder-native checkpoints and additional documentation for the 224px, 252px and 336px variants.
Please cite or link the original Birder release when using this TIMM conversion.
- Downloads last month
- 42
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support