Image Classification
Transformers
TensorBoard
Safetensors
PyTorch
vit
huggingpics
Eval Results (legacy)
Instructions to use GPTersHub/HUB_GPT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GPTersHub/HUB_GPT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="GPTersHub/HUB_GPT") 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("GPTersHub/HUB_GPT") model = AutoModelForImageClassification.from_pretrained("GPTersHub/HUB_GPT") - Notebooks
- Google Colab
- Kaggle
Hub_GPT
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.
Example Images
Hub
applemint
bazil
deal
time
- Downloads last month
- -
Evaluation results
- Accuracyself-reported0.726




