Image Classification
Transformers
PyTorch
ONNX
Safetensors
efficientnet
biology
efficientnet-b2
vision
Instructions to use dennisjooo/Birds-Classifier-EfficientNetB2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dennisjooo/Birds-Classifier-EfficientNetB2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dennisjooo/Birds-Classifier-EfficientNetB2") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("dennisjooo/Birds-Classifier-EfficientNetB2") model = AutoModelForImageClassification.from_pretrained("dennisjooo/Birds-Classifier-EfficientNetB2", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
ONNX Model for Inference
#1
by chriamue - opened
Hi, I really like this dataset and would like to use it for inference on my raspberry pi.
I had good experience with the 1 year old dataset and mobilenetv2.
Is it possible to also export this model as ONNX version?
Thank you.
Hey Chriamue!
I'm not particularly knowledgeable in converting a model to ONNX, but I tried my best, it's in the repo now.
If you need to modify it, I've made a colab notebook that you can tweak around.
Good luck with your project!
dennisjooo changed discussion status to closed