Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use Yudsky/image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yudsky/image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Yudsky/image_classification") 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("Yudsky/image_classification") model = AutoModelForImageClassification.from_pretrained("Yudsky/image_classification") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 14
Browse files- model.safetensors +1 -1
- runs/Sep06_16-13-35_0f6a57d125fc/events.out.tfevents.1725639788.0f6a57d125fc.1806.23 +3 -0
- runs/Sep06_16-13-35_0f6a57d125fc/events.out.tfevents.1725639835.0f6a57d125fc.1806.24 +3 -0
- runs/Sep06_16-13-35_0f6a57d125fc/events.out.tfevents.1725640346.0f6a57d125fc.1806.25 +3 -0
- runs/Sep06_16-13-35_0f6a57d125fc/events.out.tfevents.1725640403.0f6a57d125fc.1806.26 +3 -0
model.safetensors
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