| --- |
| language: en |
| license: cc-by-nc-4.0 |
| pipeline_tag: image-feature-extraction |
| tags: |
| - sapiens |
| --- |
| |
| # Pretrain-Sapiens-0.6B-Torchscript |
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|
| ### Model Details |
| Sapiens is a family of vision transformers pretrained on 300 million human images at 1024 x 1024 image resolution. The pretrained models, when finetuned for human-centric vision tasks, generalize to in-the-wild conditions. |
| Sapiens-0.6B natively support 1K high-resolution inference. The resulting models exhibit remarkable generalization to in-the-wild data, even when labeled data is scarce or entirely synthetic. |
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|
| - **Developed by:** Meta |
| - **Model type:** Vision Transformer |
| - **License:** Creative Commons Attribution-NonCommercial 4.0 |
| - **Task:** pretrain |
| - **Format:** torchscript |
| - **File:** sapiens_0.6b_epoch_1600_torchscript.pt2 |
|
|
| ### Model Card |
| - **Image Size:** 1024 x 1024 |
| - **Num Parameters:** 0.664 B |
| - **FLOPs:** 2.583 TFLOPs |
| - **Patch Size:** 16 x 16 |
| - **Embedding Dimensions:** 1280 |
| - **Num Layers:** 32 |
| - **Num Heads:** 16 |
| - **Feedforward Channels:** 5120 |
|
|
| ### More Resources |
| - **Repository:** [https://github.com/facebookresearch/sapiens](https://github.com/facebookresearch/sapiens) |
| - **Paper:** [https://arxiv.org/abs/2408.12569](https://arxiv.org/abs/2408.12569) |
| - **Demos:** [Sapiens Gradio Spaces](https://huggingface.co/collections/facebook/sapiens-66d22047daa6402d565cb2fc) |
| - **Project Page:** [https://about.meta.com/realitylabs/codecavatars/sapiens](https://about.meta.com/realitylabs/codecavatars/sapiens/) |
| - **Additional Results:** [https://rawalkhirodkar.github.io/sapiens](https://rawalkhirodkar.github.io/sapiens/) |
| - **HuggingFace Collection:** [https://huggingface.co/collections/facebook/sapiens-66d22047daa6402d565cb2fc](https://huggingface.co/collections/facebook/sapiens-66d22047daa6402d565cb2fc) |
|
|
| ## Uses |
| Pretrained 0.6B model can be used for feature extraction, fine-tuning, or as a starting point for training new models. |
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