Image Feature Extraction
Transformers
Safetensors
siglip_vision_model
siglip
siglip2
vision-encoder
mllm
Instructions to use LiheYoung/SigLIP-HD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LiheYoung/SigLIP-HD with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="LiheYoung/SigLIP-HD")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("LiheYoung/SigLIP-HD") model = AutoModel.from_pretrained("LiheYoung/SigLIP-HD", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 552e2aefd37839095eca5465a67572bb84f537286d8050d79c2c1af7bd440d5c
- Size of remote file:
- 1.72 GB
- SHA256:
- 462bdcaf5018115f10176894d25a577960a097375139713344713c8eff36d54a
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