Instructions to use timm/mobilenetv5_300m.gemma3n with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/mobilenetv5_300m.gemma3n with timm:
import timm model = timm.create_model("hf_hub:timm/mobilenetv5_300m.gemma3n", pretrained=True) - Transformers
How to use timm/mobilenetv5_300m.gemma3n with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="timm/mobilenetv5_300m.gemma3n")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/mobilenetv5_300m.gemma3n", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Model card for mobilenetv5_300m.gemma3n
timm MobileNetV5 image encoder only weights for the Gemma 3n series: https://huggingface.co/collections/google/gemma-3n-685065323f5984ef315c93f4
- Downloads last month
- 347
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support