Image Classification
Transformers
Safetensors
English
siglip
Structures
Desert
Glacier
Street
Ocean
Image-Classifier
art
Mountain
Instructions to use prithivMLmods/Multilabel-GeoSceneNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Multilabel-GeoSceneNet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Multilabel-GeoSceneNet") 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/Multilabel-GeoSceneNet") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Multilabel-GeoSceneNet") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -4,6 +4,9 @@ datasets:
|
|
| 4 |
- prithivMLmods/Multilabel-GeoSceneNet-16K
|
| 5 |
library_name: transformers
|
| 6 |
---
|
|
|
|
|
|
|
|
|
|
| 7 |
# **Multilabel-GeoSceneNet**
|
| 8 |
|
| 9 |
> **Multilabel-GeoSceneNet** is a vision-language encoder model fine-tuned from **google/siglip2-base-patch16-224** for **multi-label** image classification. It is designed to recognize and label multiple geographic or environmental elements in a single image using the **SiglipForImageClassification** architecture.
|
|
|
|
| 4 |
- prithivMLmods/Multilabel-GeoSceneNet-16K
|
| 5 |
library_name: transformers
|
| 6 |
---
|
| 7 |
+
|
| 8 |
+

|
| 9 |
+
|
| 10 |
# **Multilabel-GeoSceneNet**
|
| 11 |
|
| 12 |
> **Multilabel-GeoSceneNet** is a vision-language encoder model fine-tuned from **google/siglip2-base-patch16-224** for **multi-label** image classification. It is designed to recognize and label multiple geographic or environmental elements in a single image using the **SiglipForImageClassification** architecture.
|