Instructions to use prithivMLmods/Geometric-Shapes-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Geometric-Shapes-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Geometric-Shapes-Classification") 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/Geometric-Shapes-Classification") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Geometric-Shapes-Classification") - Inference
- Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -1,5 +1,7 @@
|
|
| 1 |
---
|
| 2 |
license: apache-2.0
|
|
|
|
|
|
|
| 3 |
---
|
| 4 |
```py
|
| 5 |
Classification Report:
|
|
@@ -19,4 +21,4 @@ Parallelogram ▰ 0.9926 0.9840 0.9883 1500
|
|
| 19 |
weighted avg 0.9908 0.9908 0.9907 12000
|
| 20 |
```
|
| 21 |
|
| 22 |
-

|
|
|
|
| 1 |
---
|
| 2 |
license: apache-2.0
|
| 3 |
+
datasets:
|
| 4 |
+
- prithivMLmods/Math-Shapes
|
| 5 |
---
|
| 6 |
```py
|
| 7 |
Classification Report:
|
|
|
|
| 21 |
weighted avg 0.9908 0.9908 0.9907 12000
|
| 22 |
```
|
| 23 |
|
| 24 |
+

|