How to use timm/efficientnet_b3.ra2_in1k with timm:
import timm model = timm.create_model("hf-hub:timm/efficientnet_b3.ra2_in1k", pretrained=True)
How to use timm/efficientnet_b3.ra2_in1k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="timm/efficientnet_b3.ra2_in1k") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/efficientnet_b3.ra2_in1k", device_map="auto")
Internal model structure here: https://app.svetoviz.com?bucket=timm-efficientnet-b3-ra2-in1k
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