Instructions to use KabilanM/detr-label-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KabilanM/detr-label-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="KabilanM/detr-label-detection")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("KabilanM/detr-label-detection") model = AutoModel.from_pretrained("KabilanM/detr-label-detection") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:45e302f858c4f22890dc82df81d03cda014e3f1c5bfdcb3388870dbefe32740d
|
| 3 |
+
size 165967248
|