Instructions to use sasha/dog-food-convnext-tiny-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sasha/dog-food-convnext-tiny-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sasha/dog-food-convnext-tiny-224") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("sasha/dog-food-convnext-tiny-224") model = AutoModelForImageClassification.from_pretrained("sasha/dog-food-convnext-tiny-224", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from sasha/dog-food-convnext-tiny-224: direct link, hf CLI and curl.
- Browser
- Download file 793 Bytes
-
https://huggingface.co/sasha/dog-food-convnext-tiny-224/resolve/main/README.md
- Command line
-
hf download hf://sasha/dog-food-convnext-tiny-224/README.md
-
curl -L -o README.md https://huggingface.co/sasha/dog-food-convnext-tiny-224/resolve/main/README.md
793 Bytes
metadata
tags:
- image-classification
- pytorch
- huggingpics
datasets:
- sasha/dog-food
metrics:
- accuracy
- f1
model-index:
- name: dog-food-convnext-tiny-224
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: Dog Food
type: sasha/dog-food
metrics:
- name: Accuracy
type: accuracy
value: 1
dog-food-convnext-tiny-224
This model was trained on the train split of the Dogs vs Food dataset -- try training your own using the
the demo on Google Colab!

