Instructions to use cvm2024/detr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cvm2024/detr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="cvm2024/detr")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("cvm2024/detr") model = AutoModelForObjectDetection.from_pretrained("cvm2024/detr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 1300
Browse files
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 166506812
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:360e0c5afe07a8269345e7060164f06233c43ab2e3796da36e3a7f47847ae934
|
| 3 |
size 166506812
|
runs/Apr11_07-40-51_830b0a9f1e21/events.out.tfevents.1712821254.830b0a9f1e21.319.0
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:ef5c46e1a62e057044a485a5234c87563ca92874a994385fc4ca64ea31c766d1
|
| 3 |
+
size 16372
|