Instructions to use Devarshi/Armature_Defect_Detection_All with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Devarshi/Armature_Defect_Detection_All with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Devarshi/Armature_Defect_Detection_All") 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("Devarshi/Armature_Defect_Detection_All") model = AutoModelForImageClassification.from_pretrained("Devarshi/Armature_Defect_Detection_All") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 347609873
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c8e85d9dcba8706ec2c24a9e00ae461b9ac9e46233fe5702aa7c2f13bbad6f9b
|
| 3 |
size 347609873
|
runs/Oct27_22-44-54_Devarshis-MacBook-Air.local/events.out.tfevents.1698426909.Devarshis-MacBook-Air.local.2172.0
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 sha256:5e057f2fd9aed28fd0c1daa3d084cbbb614bf9ef5ad4b8526f8df76342c7f9d1
|
| 3 |
+
size 5250
|