Image Classification
Transformers
PyTorch
TensorBoard
convnext
Generated from Trainer
Eval Results (legacy)
Instructions to use mrm8488/convnext-tiny-finetuned-beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/convnext-tiny-finetuned-beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="mrm8488/convnext-tiny-finetuned-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("mrm8488/convnext-tiny-finetuned-beans") model = AutoModelForImageClassification.from_pretrained("mrm8488/convnext-tiny-finetuned-beans") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e99e8f313dd28587f4ac51908199a1db4ad00eb7fda207a6ec5d00045e686634
- Size of remote file:
- 3.12 kB
- SHA256:
- 48067872857057041a0bbb7d56c040de2e2303dc1b2ba40ef7af701bb6ff73ed
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.