Image Classification
Transformers
PyTorch
TensorBoard
vit
vision
Generated from Trainer
Eval Results (legacy)
Instructions to use stlxx/vit-base-beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stlxx/vit-base-beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="stlxx/vit-base-beans") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("stlxx/vit-base-beans") model = AutoModelForImageClassification.from_pretrained("stlxx/vit-base-beans", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
update model card README.md
cfab7ab -
End of training
d5c9704 -
update model card README.md
94acb22 -
Model save
6592d18 -
Training in progress, epoch 5
5fa343d -
Training in progress, epoch 4
a2f28fd -
Training in progress, epoch 3
8c4bb27 -
Training in progress, epoch 2
7901b9a -
Training in progress, epoch 1
c615e4b
-
Training in progress, epoch 0
db3bc90 -
Training in progress, epoch 0
f930bcc
-
update model card README.md
5f6fcd9 -
End of training
0426e16 -
update model card README.md
dee2054 -
Model save
acd8efd -
Training in progress, epoch 5
e221a0f -
Training in progress, epoch 1
e032dd0 -
initial commit
371ec15