Model reference · open weights

nomic-embed-vision

nomic-embed-vision is an open-weight embedding model from nomic-ai, 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 nomic-ai 1 variants 59k downloads/mo
Request this model on EU hardware All served models Not on the shared API today — deployed on request.

About

What nomic-embed-vision is

nomic-embed-vision-v1.5: Expanding the Latent Space Quick Start Blog | Technical Report | AWS SageMaker | Atlas Embedding and Unstructured Data Analytics Platform nomic-embed-vision-v1.5 is a high performing vision embedding model that shares the same embedding space as nomic-embed-text-v1.5. All Nomic Embed Text models are now multimodal! Hosted Inference API The easiest way to get started with Nomic Embed is through the Nomic Embedding API. Generating embeddings with the nomic Python client is as easy as For more information, see the API reference Data Visualization Click the Nomic Atlas map below to visualize a 100,000 sample CC3M comparing the Vision and Text Embedding Space! [](https://atlas.nomic.ai/data/nomic-multimodal-series/cc3m-100k-image-bytes-v15/map) Training Details We align our vision embedder to the text embedding by employing a technique similar to LiT but instead lock the text embedder! For more details, see the Nomic Embed Vision Technical Report (soon to be released!) and corresponding blog post Training code is released in the contrastors repository Usage Remember nomic-embed-text requires prefixes and so, when using Nomic Embed in multimodal RAG scenarios (e.g. text to image retrieval), you should use the searchquery: prefix. Transformers Additionally, you can perform multimodal retrieval! Join the Nomic Community - Nomic: https://nomic.ai - Discord: https://discord.gg/myY5YDR8z8 - Twitter: https://twitter.com/nomicai

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

Specifications

What it is

Makernomic-ai
TypeEmbedding models
Parameters (lead)93M
Variants1
Runs withtransformers
Released2024-06-01
Popularity59k downloads / month
Likes225
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
nomic-embed-vision-v1.593MBF16~0.2 GBWeights ↗

Using it via the API

Call it like any OpenAI endpoint

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

Details

Languages, data & research

Languages

en

Tags

transformers onnx safetensors nomic_bert feature-extraction image-feature-extraction custom_code en

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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