Long-CLIP: Unlocking the Long-Text Capability of CLIP
Paper • 2403.15378 • Published • 4
Configuration Parsing Warning:Config file config.json cannot be fetched (too big)
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
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
- Original Weight: LongCLIP-B16
- Resolution: 3x224x224
- Support Cooper version:
- Cooper SDK: [2.5.4]
- Cooper Foundry: [2.3]
| Model | Device | Model Link |
|---|---|---|
| LongCLIP-B16 Image Encoder | N1-655 | Model_Link |
| LongCLIP-B16 Text Encoder | N1-655 | Model_Link |
| LongCLIP-B16 Image encoder | X7 | Model_Link |
| LongCLIP-B16 Text Encoder | X7 | Model_Link |
| LongCLIP-B16 Image encoder | CV7 | Model_Link |
| LongCLIP-B16 Text Encoder | CV7 | Model_Link |
| LongCLIP-B16 Image encoder | CV72 | Model_Link |
| LongCLIP-B16 Text Encoder | CV72 | Model_Link |
| LongCLIP-B16 Image encoder | CV75 | Model_Link |
| LongCLIP-B16 Text Encoder | CV75 | Model_Link |
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