Clip Vit Large Patch14 GGUF

--- 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. ## Provenance and EU AI Act Art. 53 note - **Upstream model:** [openai/clip-vit-large-patch14](https://huggingface.co/openai/clip-vit-large-patch14) — published by `openai`. - **Upstream licence:** `mit`. 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 — where it is documented at all — 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.

Source context: 59 downloads · 1 likes · Pipeline image-feature-extraction · Library ggml · Repo cstr/clip-vit-large-patch14-GGUF

Source context: 188 downloads · 1 likes · Pipeline image-feature-extraction · Library ggml · Repo cstr/clip-vit-large-patch14-GGUF