# Load model directly
from transformers import AutoImageProcessor, VisionTransformerForImageClassification
processor = AutoImageProcessor.from_pretrained("bswift/test")
model = VisionTransformerForImageClassification.from_pretrained("bswift/test")Quick Links
ch-observations-12-12-2023-200530
Description
Fine-tuned vit_large_patch16 model for ch-observations-12-12-2023-200530
Use Cases
- Use case 1
- Use case 2
Limitations
- Limitation 1
- Limitation 2
Ethics
- Ethics 1
- Ethics 2
Training Data
420 images from 9 classes
Training Procedure
Fine-tuned for 1 epochs with batch size 10 and base learning rate 0.005
Intended Use
Intended for use with ch-observations
Authors
- Author 1
- Author 2
References
- Reference 1
- Reference 2
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="bswift/test") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")