metadata
license: mit
tags:
- clip
- vision
- gguf
- crispembed
- image-embedding
pipeline_tag: image-feature-extraction
library_name: ggml
CLIP ViT-L/14 Vision Encoder (GGUF)
GGUF conversion of openai/clip-vit-large-patch14 for use with CrispEmbed.
- Architecture: CLIP ViT-L/14 vision encoder
- Parameters: 304M
- Output: 768-dimensional L2-normalized embeddings (1024d internal, projected to 768d)
- Input: 224x224 RGB image with CLIP normalization
- Size: ~1.2 GB
- Source: openai/clip-vit-large-patch14
Usage
# Embed a single image
crispembed -m clip-vit-large-patch14 --image photo.jpg
# Batch processing
crispembed -m clip-vit-large-patch14 --image-dir ./photos/ --output embeddings.bin
Cross-modal pairing
Shares an embedding space with cstr/clip-text-large-GGUF for zero-shot image-text matching.
Notes
- All output embeddings are L2-normalized.
- This is a GGUF conversion; weights are numerically equivalent to the original HuggingFace model.