Instructions to use hf-internal-testing/tiny-random-DetrForObjectDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-DetrForObjectDetection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="hf-internal-testing/tiny-random-DetrForObjectDetection")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-DetrForObjectDetection") model = AutoModelForObjectDetection.from_pretrained("hf-internal-testing/tiny-random-DetrForObjectDetection") - Notebooks
- Google Colab
- Kaggle
Upload ONNX weights (#2)
Browse files- [Awaiting approval] Upload ONNX weights (73c6a0e2e91896954e7ed3b3b659c33a558e5ed9)
- onnx/model.onnx +3 -0
onnx/model.onnx
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:92dbe06deaf370698a0842b7f589b279b5cda2cbd741265db29e4018315dcb33
|
| 3 |
+
size 103326338
|