Instructions to use hf-internal-testing/tiny-random-GroundingDinoForObjectDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-GroundingDinoForObjectDetection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-object-detection", model="hf-internal-testing/tiny-random-GroundingDinoForObjectDetection")# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotObjectDetection processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-GroundingDinoForObjectDetection") model = AutoModelForZeroShotObjectDetection.from_pretrained("hf-internal-testing/tiny-random-GroundingDinoForObjectDetection") - Notebooks
- Google Colab
- Kaggle
Update preprocessor_config.json
Browse files- preprocessor_config.json +2 -2
preprocessor_config.json
CHANGED
|
@@ -21,7 +21,7 @@
|
|
| 21 |
"resample": 2,
|
| 22 |
"rescale_factor": 0.00392156862745098,
|
| 23 |
"size": {
|
| 24 |
-
"
|
| 25 |
-
"
|
| 26 |
}
|
| 27 |
}
|
|
|
|
| 21 |
"resample": 2,
|
| 22 |
"rescale_factor": 0.00392156862745098,
|
| 23 |
"size": {
|
| 24 |
+
"width": 800,
|
| 25 |
+
"height": 800
|
| 26 |
}
|
| 27 |
}
|