Instructions to use timm/ViT-SO400M-16-SigLIP2-384 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- OpenCLIP
How to use timm/ViT-SO400M-16-SigLIP2-384 with OpenCLIP:
import open_clip model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms('hf-hub:timm/ViT-SO400M-16-SigLIP2-384') tokenizer = open_clip.get_tokenizer('hf-hub:timm/ViT-SO400M-16-SigLIP2-384') - Notebooks
- Google Colab
- Kaggle
| { | |
| "model_cfg": { | |
| "embed_dim": 1152, | |
| "init_logit_bias": -10, | |
| "custom_text": true, | |
| "vision_cfg": { | |
| "image_size": 384, | |
| "timm_model_name": "vit_so400m_patch16_siglip_384", | |
| "timm_model_pretrained": false, | |
| "timm_pool": "map", | |
| "timm_proj": "none" | |
| }, | |
| "text_cfg": { | |
| "context_length": 64, | |
| "vocab_size": 256000, | |
| "hf_tokenizer_name": "timm/ViT-SO400M-16-SigLIP2-384", | |
| "tokenizer_kwargs": { | |
| "clean": "canonicalize" | |
| }, | |
| "width": 1152, | |
| "heads": 16, | |
| "layers": 27, | |
| "mlp_ratio": 3.7362, | |
| "no_causal_mask": true, | |
| "proj_bias": true, | |
| "pool_type": "last", | |
| "norm_kwargs": { | |
| "eps": 1e-06 | |
| }, | |
| "act_kwargs": { | |
| "approximate": "tanh" | |
| } | |
| } | |
| }, | |
| "preprocess_cfg": { | |
| "mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "interpolation": "bicubic", | |
| "resize_mode": "squash" | |
| } | |
| } |