Model reference · open weights

vit_base_patch16_224.dino

vit_base_patch16_224.dino is an open-weight embedding model from timm, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.

Embeddings timm 1 variants 143k downloads/mo
Request this model on EU hardware All served models Not on the shared API today — deployed on request.

About

What vit_base_patch16_224.dino is

Model card for vitbasepatch16224.dino A Vision Transformer (ViT) image feature model. Trained with Self-Supervised DINO method. Model Details - Model Type: Image classification / feature backbone - Model Stats: - Params (M): 85.8 - GMACs: 16.9 - Activations (M): 16.5 - Image size: 224 x 224 - Papers: - Emerging Properties in Self-Supervised Vision Transformers: https://arxiv.org/abs/2104.14294 - An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale: https://arxiv.org/abs/2010.11929v2 - Pretrain Dataset: ImageNet-1k - Original: https://github.com/facebookresearch/dino Model Usage Image Classification Image Embeddings Model Comparison Explore the dataset and runtime metrics of this model in timm model results. Citation

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

Makertimm
TypeEmbedding models
Parameters (lead)86M
Variants1
Runs withtimm
Released2022-12-22
Popularity143k downloads / month
Likes6
LicenceOpen weights

How it works

How embedding models work

Your textsentence / documentEncodermaps meaningVectorlist of numbersAn embedding model turns text into a vector, so similar meanings sit close together — the basis of search and RAG.

Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

VariantParamsPrecisionVRAMFits 16 GBWeights
vit_base_patch16_224.dino86MBF16~0.2 GBWeights ↗

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys vit-base-patch16-224-dino for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (vit-base-patch16-224-dino below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/embeddings \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"vit-base-patch16-224-dino","input":"text to embed"}'

Details

Languages, data & research

Tags

timm pytorch safetensors image-feature-extraction transformers

Papers

Licence

Open weights

Open weights under apache-2.0 — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗

Sources

Weights & code

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