Instructions to use hustvl/yolos-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hustvl/yolos-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="hustvl/yolos-tiny")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("hustvl/yolos-tiny") model = AutoModelForObjectDetection.from_pretrained("hustvl/yolos-tiny") - Notebooks
- Google Colab
- Kaggle
Question for @hustvl: mobile deployment?
#11
by 3morixd - opened
Great work on this model! π
At Dispatch AI (FZE, UAE), we benchmark models on 40 phones (Snapdragon 865). We're always looking for models that can run on mobile.
Question for @hustvl (or anyone who's tested this):
- What's the expected inference speed on ARM processors?
- Has anyone quantized this to GGUF/ONNX?
- What's the minimum RAM needed?
If you're interested, we'd love to benchmark it on our phone farm and share results publicly.
- Dispatch AI (FZE), Sharjah UAE