Instructions to use emvecchi/umod_constructiveness with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use emvecchi/umod_constructiveness with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("roberta-base") model.load_adapter("emvecchi/umod_constructiveness", set_active=True) - Notebooks
- Google Colab
- Kaggle
Upload 4 files
Browse files- pytorch_adapter.bin +1 -1
- pytorch_model_head.bin +1 -1
pytorch_adapter.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 3594901
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b49006fe0d44cdb6a784b0aefee3c441c9343ce383028ab0374be291c84d327d
|
| 3 |
size 3594901
|
pytorch_model_head.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 2366943
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:61b427f857fb6f6b4aa415fdc5ea179478b9f1d754ac9550977b920d8af34cfe
|
| 3 |
size 2366943
|