Model reference · open weights

vit_large_patch14_dino.lvd

vit_large_patch14_dino.lvd 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 170k downloads/mo
Request this model on EU hardware All served models Not on the shared API today — deployed on request.

About

What vit_large_patch14_dino.lvd is

Model card for vitlargepatch14dinov2.lvd142m A Vision Transformer (ViT) image feature model. Pretrained on LVD-142M with self-supervised DINOv2 method. Model Details - Model Type: Image classification / feature backbone - Model Stats: - Params (M): 304.4 - GMACs: 507.1 - Activations (M): 1058.8 - Image size: 518 x 518 - Papers: - DINOv2: Learning Robust Visual Features without Supervision: https://arxiv.org/abs/2304.07193 - An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale: https://arxiv.org/abs/2010.11929v2 - Original: https://github.com/facebookresearch/dinov2 - Pretrain Dataset: LVD-142M 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)304M
Variants1
Runs withtimm
Released2023-05-09
Popularity170k downloads / month
Likes17
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_large_patch14_dinov2.lvd142m304MBF16~0.7 GBWeights ↗

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys vit-large-patch14-dino-lvd for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (vit-large-patch14-dino-lvd 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-large-patch14-dino-lvd","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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Explore

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