Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use dingusagar/vit-base-avengers-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dingusagar/vit-base-avengers-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dingusagar/vit-base-avengers-v2") 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("dingusagar/vit-base-avengers-v2") model = AutoModelForImageClassification.from_pretrained("dingusagar/vit-base-avengers-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cbb130c0294813d7e456f55359727f89f665977f0d9a3bb9a28ed385e6faa186
- Size of remote file:
- 4.73 kB
- SHA256:
- e4cc03a6317392674771736f9310fac0be705bbb653b78c892e6c6f061e7fc7c
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