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README.md

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+---
+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.