README.md

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library_name: pytorch
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![longclip_logo](resource/LongCLIP.png)

LongCLIP extends the CLIP vision–language framework to support significantly longer text inputs, enabling richer contextual understanding while preserving strong image–text alignment.

Original paper: [Long-CLIP: Unlocking Long-Text Capability in CLIP, Zhang et al., 2024](https://arxiv.org/abs/2403.15378)

# LongCLIP-B16

This model uses the LongCLIP B/16 variant, which is based on a ViT-Base backbone with 16×16 image patches and enhanced long-text encoding capacity. It is well suited for vision–language applications such as image retrieval, zero-shot classification, and multimodal reasoning where long textual prompts or descriptions are important.

Model Configuration:
- Reference implementation: [LongCLIP-B16](https://github.com/beichenzbc/Long-CLIP)
- Original Weight: [LongCLIP-B16](https://huggingface.co/BeichenZhang/LongCLIP-B/blob/main/longclip-B.pt)
- Resolution: 3x224x224
- Support Cooper version:
    - Cooper SDK: [2.5.2]
    - Cooper Foundry: [2.2]

| Model | Device | Model Link |
| :-----: | :-----: | :-----: |
| LongCLIP-B16 Image Encoder | N1-655 | [Model_Link](https://huggingface.co/Ambarella/LongCLIP/blob/main/n1-655_longclip_base_patch16_image_encoder.bin) |
| LongCLIP-B16 Text Encoder | N1-655 | [Model_Link](https://huggingface.co/Ambarella/LongCLIP/blob/main/n1-655_longclip_base_patch16_text_encoder.bin) |
| LongCLIP-B16 Image encoder | CV72 | [Model_Link](https://huggingface.co/Ambarella/LongCLIP/blob/main/cv72_longclip_base_patch16_image_encoder.bin) |
| LongCLIP-B16 Text Encoder | CV72 | [Model_Link](https://huggingface.co/Ambarella/LongCLIP/blob/main/cv72_longclip_base_patch16_text_encoder.bin) |
| LongCLIP-B16 Image encoder | CV75 | [Model_Link](https://huggingface.co/Ambarella/LongCLIP/blob/main/cv75_longclip_base_patch16_image_encoder.bin) |
| LongCLIP-B16 Text Encoder | CV75 | [Model_Link](https://huggingface.co/Ambarella/LongCLIP/blob/main/cv75_longclip_base_patch16_text_encoder.bin) |