Instructions to use facebook/regnet-x-006 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/regnet-x-006 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="facebook/regnet-x-006") 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("facebook/regnet-x-006") model = AutoModelForImageClassification.from_pretrained("facebook/regnet-x-006") - Notebooks
- Google Colab
- Kaggle
Add TF weights (#1)
Browse files- Add TF weights (30435bdb0a1ca2621d57b7881dbd5f6cf72518eb)
Co-authored-by: Joao Gante <joaogante@users.noreply.huggingface.co>
- tf_model.h5 +3 -0
tf_model.h5
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:a23824ca7334c442f5f12be24ead78d2ff57a08ca609b06f4ea33c7c1e95a11c
|
| 3 |
+
size 25234016
|