Image Classification
Transformers
TensorBoard
Safetensors
vit
vision
Generated from Trainer
Eval Results (legacy)
Instructions to use phonghoccode/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use phonghoccode/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="phonghoccode/results") 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("phonghoccode/results") model = AutoModelForImageClassification.from_pretrained("phonghoccode/results") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 76d9d6e0f54a1b43944e03912363f1bd2aaf65b8636f9316d5a158af2b7e1eeb
- Size of remote file:
- 343 MB
- SHA256:
- 4e4034e5d703a876e2fd7ce1747a29671deb73538a487d3aa3c85a4b2240c73e
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