Clip Vit Base Patch16 GGUF

--- license: mit tags: - clip - vision - gguf - crispembed - image-embedding pipeline_tag: image-feature-extraction library_name: ggml --- # CLIP ViT-B/16 Vision Encoder (GGUF) GGUF conversion of [openai/clip-vit-base-patch16](https://huggingface.co/openai/clip-vit-base-patch16) for use with [CrispEmbed](https://github.com/CrispStrobe/CrispEmbed). - **Architecture:** CLIP ViT-B/16 vision encoder - **Parameters:** 86M - **Output:** 512-dimensional L2-normalized embeddings (768d internal, projected to 512d via visual_projection) - **Input:** 224x224 RGB image with CLIP normalization - **Size:** ~329 MB - **Source:** openai/clip-vit-base-patch16 ## Usage ```bash # Embed a single image crispembed -m clip-vit-base-patch16 --image photo.jpg # Batch processing crispembed -m clip-vit-base-patch16 --image-dir ./photos/ --output embeddings.bin ``` ## Cross-modal pairing This model shares an embedding space with [cstr/clip-text-base-GGUF](https://huggingface.co/cstr/clip-text-base-GGUF). Use both to perform zero-shot image-text matching: ```bash crispembed -m clip-vit-base-patch16 --image photo.jpg # vision embedding crispembed -m clip-text-base "a photo of a cat" # text embedding ``` Cosine similarity between the two outputs measures image-text alignment. ## 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-base-patch16](https://huggingface.co/openai/clip-vit-base-patch16) — 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-purp...

Source context: 18 downloads · 0 likes · Pipeline image-feature-extraction · Library ggml · Repo cstr/clip-vit-base-patch16-GGUF

Source context: 35 downloads · 0 likes · Pipeline image-feature-extraction · Library ggml · Repo cstr/clip-vit-base-patch16-GGUF