Instructions to use bobox/DeBERTa-ST-AllLayers-v3.2-checkpoints-tmp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bobox/DeBERTa-ST-AllLayers-v3.2-checkpoints-tmp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="bobox/DeBERTa-ST-AllLayers-v3.2-checkpoints-tmp")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("bobox/DeBERTa-ST-AllLayers-v3.2-checkpoints-tmp") model = AutoModel.from_pretrained("bobox/DeBERTa-ST-AllLayers-v3.2-checkpoints-tmp") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 2864
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 565251810
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d70c18dedfac397461b64eb6885c0b53813a253749724a6b10e2d7cc07141ea5
|
| 3 |
size 565251810
|
runs/Jul13_05-43-48_962250ad82c3/events.out.tfevents.1720849452.962250ad82c3.4274.0
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:08903e77af350cdebbad801a69fe2f0a4116102bdeb73ece4d2cb483b15bd9c5
|
| 3 |
+
size 131938
|