Model reference · open weights

tips-so400m14

tips-so400m14 is an open-weight embedding model from google, 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 google 1 variants 267k downloads/mo
Request this model on EU hardware All served models Not on the shared API today — deployed on request.

About

What tips-so400m14 is

TIPSv2 — SO400m/14 TIPSv2 (Text-Image Pre-training with Spatial awareness) is a family of contrastive vision-language models that produce spatially rich image features aligned with text embeddings. This is the SO400m variant with 412M vision params and 448M text params. Try the code snippets below or check out the GitHub repo for more use cases and visualizations, including zero-shot segmentation. Usage Load the model Encode images Images should be tensors in [0, 1] range (just ToTensor(), no ImageNet normalization). Encode text Zero-shot classification Visualize spatial features GPU inference Model details - Architecture: ViT vision encoder (27 layers) + Transformer text encoder (27 layers) - Image preprocessing: resize to any resolution, convert to [0, 1] (no ImageNet normalization) - Text preprocessing: SentencePiece tokenizer, lowercased, max 64 tokens - Patch size: 14x14 pixels License Apache 2.0 Citation

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

Specifications

What it is

Makergoogle
TypeEmbedding models
Parameters (lead)862M
Variants1
Runs withtransformers
Released2026-04-09
Popularity267k downloads / month
Likes18
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
tipsv2-so400m14862MBF16~2 GBWeights ↗

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys tips-so400m14 for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (tips-so400m14 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":"tips-so400m14","input":"text to embed"}'

Details

Languages, data & research

Tags

transformers safetensors tipsv2 feature-extraction vision image-text contrastive-learning zero-shot zero-shot-image-classification custom_code

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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