| 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](https://huggingface.co/openai/clip-vit-large-patch14) for use with [CrispEmbed](https://github.com/CrispStrobe/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 | |
| ```bash | |
| # 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](https://huggingface.co/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. | |