Instructions to use NTCAL/SavedAfterTrainingTest39 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NTCAL/SavedAfterTrainingTest39 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NTCAL/SavedAfterTrainingTest39")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NTCAL/SavedAfterTrainingTest39") model = AutoModelForSequenceClassification.from_pretrained("NTCAL/SavedAfterTrainingTest39") - Notebooks
- Google Colab
- Kaggle
Commit ·
be6037a
1
Parent(s): 36771e2
Training in progress, epoch 1
Browse files- pytorch_model.bin +1 -1
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 498161013
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b258c9037e7b97a4b283d07399b22524581cf69f06f1f60dbc185cd54bd13a03
|
| 3 |
size 498161013
|