nomic-embed-vision-v1.5 — GGUF for CrispEmbed
GGUF conversion of nomic-ai/nomic-embed-vision-v1.5 (Apache-2.0, © Nomic AI) for CrispEmbed. It embeds images into the same space as nomic-embed-text-v1.5, so text can search images.
| file | size | precision |
|---|---|---|
nomic-embed-vision-v1.5-f16.gguf | 188 MB | F16 weights (norms, biases, position embeddings in F32) |
nomic-embed-vision-v1.5-f32.gguf | 372 MB | F32 |
crispembed -m nomic-embed-vision-v1.5 --image photo.jpg # 768-d, L2-normalised
crispembed -m nomic-embed-text-v1.5 "search_query: a photo of a cat"
For cross-modal scoring, the upstream model card applies a parameter-free LayerNorm (subtract the mean, divide by the standard deviation) to the text embedding before L2 normalisation.
Parity
Checked against transformers (NomicVisionModel, trust_remote_code) with
tools/ci-heavy/nomic_vision.py.
The cosine between C++ and transformers embeddings was 1.000000 on all four test images, for both files. That holds both
for the processor's exact pixels and through CrispEmbed's own image loader.
Converted with models/convert-nomic-vision-to-gguf.py. The original model's licence and
attribution apply.