Instructions to use ArrayDice/Vehicle_Detection_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArrayDice/Vehicle_Detection_Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="ArrayDice/Vehicle_Detection_Model")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("ArrayDice/Vehicle_Detection_Model") model = AutoModelForObjectDetection.from_pretrained("ArrayDice/Vehicle_Detection_Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 8
Browse files
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 166505112
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:25ac94a36f204fa4694793cc6e249f34a596d090bedddec61e68fa19c4cada34
|
| 3 |
size 166505112
|
runs/Jul11_13-04-08_9002a8dd5626/events.out.tfevents.1720703068.9002a8dd5626.417.0
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:bf55aa6480ff88c8b1283eabf009bd241df048a485c6b1c3c66cffefffc2d11e
|
| 3 |
+
size 18969
|