lhbit20010120/llava_eval_czr
SigLIP (shape-optimized model) SigLIP model pre-trained on WebLi at resolution 384x384. It was introduced in the paper Sigmoid Loss for Language Image Pre-Training by Zhai et al. and first released in this repository. This model has the SoViT-400m architecture, which is the shape-optimized version as presented in Getting ViT in Shape: Scaling Laws for Compute-Optimal Model Design by Alabdulmohsin et al. Disclaimer: The team releasing SigLIP did not write a model card for this… See the full description on the dataset page: https://huggingface.co/datasets/lhbit20010120/llava_eval_czr.
| Author / organization | lhbit20010120 |
|---|---|
| License (as declared) | apache-2.0 |
| Downloads | 152 (as reported by Hugging Face) |
| Likes | 0 |
| Created | 5 October 2024 |
| Last updated at source | 2 December 2024 |
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- 17 Oct 2026 Description: SigLIP (shape-optimized model) SigLIP model pre-trained on WebLi at resolution 384x384. It was introduced in the paper Sigmoid Loss for Language Image Pre-Training by Zhai et al. and first released in this repository. This model has the SoV → SigLIP (shape-optimized model) SigLIP model pre-trained on WebLi at resolution 384x384. It was introduced in the paper Sigmoid Loss for Language Image Pre-Training by Zhai et al. and first released in this repository. This model has the SoV
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