Instructions to use binitt/detr-resnet-50_finetuned_cppe5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use binitt/detr-resnet-50_finetuned_cppe5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="binitt/detr-resnet-50_finetuned_cppe5")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("binitt/detr-resnet-50_finetuned_cppe5") model = AutoModelForObjectDetection.from_pretrained("binitt/detr-resnet-50_finetuned_cppe5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 600
Browse files
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 166498936
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:1425756f9173604805d18288dc11faf1f2777f9ef013d8cc39784119d8a6baec
|
| 3 |
size 166498936
|
runs/Feb14_05-43-30_b34d5e62acde/events.out.tfevents.1707889411.b34d5e62acde.2130.0
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:e893e9a191a8cf7cd47546a0e9e1b9d996e44a85f1fd301b7baffc74a3d0bcff
|
| 3 |
+
size 6864
|