Instructions to use suous/recnext_a0.dist_300e_in1k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use suous/recnext_a0.dist_300e_in1k with timm:
import timm model = timm.create_model("hf_hub:suous/recnext_a0.dist_300e_in1k", pretrained=True) - Transformers
How to use suous/recnext_a0.dist_300e_in1k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="suous/recnext_a0.dist_300e_in1k") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("suous/recnext_a0.dist_300e_in1k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 133 Bytes
d2cb1bb | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:d6b002a7d848b837598caaf274c0a8ad5445b5bed80f7ea8a7544c07042570cc
size 12827766
|