huggan/inat_butterflies_top10k
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How to use SoulPerforms/Butterfly_image_classification_resnet18 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("image-classification", model="SoulPerforms/Butterfly_image_classification_resnet18")
pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png") # Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("SoulPerforms/Butterfly_image_classification_resnet18", dtype="auto")Butterfly image classification model that use pre-trained cnn model resnet18 and fine-tuned the last fully connected layer to classify 75 categories of butterfly species.
The model used the best checkpoint with 90% test accuracy.
The model constructed on Pytorch environment.
Epoch: 28 Train Loss: 0.17 Train Accuracy: 0.96 Test Accuracy: 0.90