SigLIP SoViT-400M/14 Vision Encoder 384px (GGUF)
GGUF conversion of google/siglip-so400m-patch14-384 for use with CrispEmbed.
- Architecture: SigLIP SoViT-400M/14 vision encoder (shape-optimized)
- Parameters: 428M
- Output: 1152-dimensional L2-normalized embeddings
- Input: 384x384 RGB image with SigLIP normalization (mean=0.5, std=0.5)
- Patch size: 14
- Size: ~1.6 GB
- Source: google/siglip-so400m-patch14-384
Usage
# Embed a single image
crispembed -m siglip-so400m-patch14-384 --image photo.jpg
# Batch processing
crispembed -m siglip-so400m-patch14-384 --image-dir ./photos/ --output embeddings.bin
About SigLIP SoViT-400M
SoViT-400M is a shape-optimized SigLIP variant that redistributes compute across width, depth, and MLP ratio for better efficiency. Combined with 384px input and patch size 14, it provides high-quality vision embeddings.
Notes
- All output embeddings are L2-normalized.
- This is a GGUF conversion; weights are numerically equivalent to the original HuggingFace model.
Provenance and EU AI Act Art. 53 note
- Upstream model: google/siglip-so400m-patch14-384 โ published by
google. - Upstream licence:
apache-2.0. This repository redistributes under the same terms; it grants no rights the upstream licence does not. - What was done here: format conversion and/or quantisation only (GGUF/GGML). No training, no fine-tuning, no merging, no distillation, no change to architecture, vocabulary or capability. Only the numeric representation of the upstream weights differs.
- Training data: documented โ where it is documented at all โ by the upstream provider; see the upstream model card. No training data was used, added or selected by this repository.
- Provider status: under Regulation (EU) 2024/1689 the upstream authors remain the provider of this model. Converting the serialisation format does not make this repository the provider of a new general-purpose AI model, and no such claim is made. Questions about training content, copyright policy or model capability belong upstream.
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