Image Classification
Transformers
TensorBoard
Safetensors
vit
vision
Generated from Trainer
Eval Results (legacy)
Instructions to use amunchet/rorshark-vit-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amunchet/rorshark-vit-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="amunchet/rorshark-vit-base") 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("amunchet/rorshark-vit-base") model = AutoModelForImageClassification.from_pretrained("amunchet/rorshark-vit-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
8736519 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:ffcc3f59e70812095756ed77abfa7f9b0700337a7c9d25983e9245c2dc331049
size 4728
|