Image Classification
Transformers
Safetensors
English
siglip
Cat
Dog
Classification
SigLIP2
Vision-encoder
Instructions to use prithivMLmods/PussyCat-vs-Doggie-SigLIP2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/PussyCat-vs-Doggie-SigLIP2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/PussyCat-vs-Doggie-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/PussyCat-vs-Doggie-SigLIP2") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/PussyCat-vs-Doggie-SigLIP2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -2,4 +2,18 @@
|
|
| 2 |
license: apache-2.0
|
| 3 |
datasets:
|
| 4 |
- Siraitia/deeplearning-catdog
|
| 5 |
-
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 2 |
license: apache-2.0
|
| 3 |
datasets:
|
| 4 |
- Siraitia/deeplearning-catdog
|
| 5 |
+
---
|
| 6 |
+
|
| 7 |
+
```py
|
| 8 |
+
Classification Report:
|
| 9 |
+
precision recall f1-score support
|
| 10 |
+
|
| 11 |
+
Pussy Cat 0.9194 0.8745 0.8964 12500
|
| 12 |
+
Doggie 0.8803 0.9234 0.9013 12500
|
| 13 |
+
|
| 14 |
+
accuracy 0.8989 25000
|
| 15 |
+
macro avg 0.8999 0.8989 0.8989 25000
|
| 16 |
+
weighted avg 0.8999 0.8989 0.8989 25000
|
| 17 |
+
```
|
| 18 |
+
|
| 19 |
+

|