Instructions to use dsupa/retinaface with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dsupa/retinaface with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dsupa/retinaface", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files- config.json +6 -0
- model.pth +3 -0
config.json
ADDED
|
@@ -0,0 +1,6 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"in_channel": 32,
|
| 3 |
+
"out_channel": 64,
|
| 4 |
+
"_model_cls_name": "RetinaFaceModel",
|
| 5 |
+
"_config_cls_name": "RetinaFaceModelConfig"
|
| 6 |
+
}
|
model.pth
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:4c53197bc707444b109f217843cf82bb9477a536ba709e6482c7065a9885d59c
|
| 3 |
+
size 1814138
|