Image Classification
Transformers
PyTorch
TensorFlow
TensorBoard
Safetensors
timm_wrapper
vision
Generated from Trainer
Instructions to use amyeroberts/vit-base-beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amyeroberts/vit-base-beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="amyeroberts/vit-base-beans") 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("amyeroberts/vit-base-beans") model = AutoModelForImageClassification.from_pretrained("amyeroberts/vit-base-beans") - Notebooks
- Google Colab
- Kaggle
| timestamp,experiment_id,project_name,duration,emissions,energy_consumed,country_name,country_iso_code,region,on_cloud,cloud_provider,cloud_region | |
| 2024-09-30T20:12:46,a1b98ce0-5999-43a7-ae1d-c76c57ba4514,codecarbon,89.43079400062561,0.0007095535156443428,0.0010557118809902488,United Kingdom,GBR,england,N,, | |