Instructions to use nvidia/mit-b5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/mit-b5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nvidia/mit-b5") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("nvidia/mit-b5") model = AutoModelForImageClassification.from_pretrained("nvidia/mit-b5") - Inference
- Notebooks
- Google Colab
- Kaggle
Remove reshape_last_stage
Browse files- config.json +0 -1
config.json
CHANGED
|
@@ -2053,7 +2053,6 @@
|
|
| 2053 |
3,
|
| 2054 |
3
|
| 2055 |
],
|
| 2056 |
-
"reshape_last_stage": false,
|
| 2057 |
"sr_ratios": [
|
| 2058 |
8,
|
| 2059 |
4,
|
|
|
|
| 2053 |
3,
|
| 2054 |
3
|
| 2055 |
],
|
|
|
|
| 2056 |
"sr_ratios": [
|
| 2057 |
8,
|
| 2058 |
4,
|