Instructions to use mariamhsein16/FacialExpressionDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mariamhsein16/FacialExpressionDetection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="mariamhsein16/FacialExpressionDetection") 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("mariamhsein16/FacialExpressionDetection") model = AutoModelForImageClassification.from_pretrained("mariamhsein16/FacialExpressionDetection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files
runs/Jan21_13-54-14_r-mariamhsein16-image-classification-gf62sciv-fa6a8-ggg5t/events.out.tfevents.1769003656.r-mariamhsein16-image-classification-gf62sciv-fa6a8-ggg5t.59.0
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:1f844c7519dda5c1c9f124621f93b3d9ae21d49a18bbe5742a78f8b906b1f9ff
|
| 3 |
+
size 7695
|