Instructions to use whyoke/object_detection_test_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use whyoke/object_detection_test_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="whyoke/object_detection_test_1")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("whyoke/object_detection_test_1") model = AutoModelForObjectDetection.from_pretrained("whyoke/object_detection_test_1") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 2200
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 166620197
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:69dcf986f1ee9dd6cb55897c3bf097213b5e7230938c1f15908eb71c89a1947b
|
| 3 |
size 166620197
|
runs/Mar26_22-33-10_yokz-labtop/events.out.tfevents.1679844805.yokz-labtop.15052.0
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 sha256:24720cb9a066183ed7228a9f6a12ff6774dc31b79be9166dc4e45e3adc0034a7
|
| 3 |
+
size 11454
|