Instructions to use SummerChiam/rust_image_classification_7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SummerChiam/rust_image_classification_7 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="SummerChiam/rust_image_classification_7") 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("SummerChiam/rust_image_classification_7") model = AutoModelForImageClassification.from_pretrained("SummerChiam/rust_image_classification_7", device_map="auto") - Notebooks
- Google Colab
- Kaggle
|
Download README.md from SummerChiam/rust_image_classification_7: direct link, hf CLI and curl.
- Browser
- Download file 762 Bytes
-
https://huggingface.co/SummerChiam/rust_image_classification_7/resolve/main/README.md
- Command line
-
hf download hf://SummerChiam/rust_image_classification_7/README.md
-
curl -L -o README.md https://huggingface.co/SummerChiam/rust_image_classification_7/resolve/main/README.md
762 Bytes
metadata
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
model-index:
- name: rust_image_classification_7
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9645569324493408
rust_image_classification_7
Autogenerated by HuggingPics🤗🖼️
Create your own image classifier for anything by running the demo on Google Colab.
Report any issues with the demo at the github repo.

