Image Classification
Transformers
Safetensors
English
siglip
Human
Non-Human
Detection
SigLIP2
Vision-Encoder
Instructions to use prithivMLmods/Human-vs-NonHuman-Detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Human-vs-NonHuman-Detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Human-vs-NonHuman-Detection") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/Human-vs-NonHuman-Detection") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Human-vs-NonHuman-Detection") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
e01a0c7 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:206d195b28a5a4e1f61804a2eec06b109a4be9fa8d841f4d552fca404cebe15f
size 5304
|