Instructions to use prithivMLmods/RESISC45-SigLIP2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/RESISC45-SigLIP2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/RESISC45-SigLIP2") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/RESISC45-SigLIP2") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/RESISC45-SigLIP2") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -11,6 +11,7 @@ library_name: transformers
|
|
| 11 |
tags:
|
| 12 |
- RESISC45
|
| 13 |
- SigLIP2
|
|
|
|
| 14 |
---
|
| 15 |
|
| 16 |

|
|
|
|
| 11 |
tags:
|
| 12 |
- RESISC45
|
| 13 |
- SigLIP2
|
| 14 |
+
- Image-Classification
|
| 15 |
---
|
| 16 |
|
| 17 |

|