Image Classification
Transformers
PyTorch
TensorBoard
Safetensors
convnext
Generated from Trainer
CV
ConvNeXT
satellite
EuroSAT
Eval Results (legacy)
Instructions to use mrm8488/convnext-tiny-finetuned-eurosat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/convnext-tiny-finetuned-eurosat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="mrm8488/convnext-tiny-finetuned-eurosat") 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-eurosat") model = AutoModelForImageClassification.from_pretrained("mrm8488/convnext-tiny-finetuned-eurosat", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 454afea38cd33e98027115577fe5423bf3ce7518014477990863e8ab9fe1d30c
- Size of remote file:
- 111 MB
- SHA256:
- 0b28ec8a2f5a567ba15ec5aac663ef5345626c5b454e249fb38f93a139cd1650
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.