Instructions to use Andranik/TestPytorchClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Andranik/TestPytorchClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Andranik/TestPytorchClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Andranik/TestPytorchClassification") model = AutoModelForSequenceClassification.from_pretrained("Andranik/TestPytorchClassification") - Notebooks
- Google Colab
- Kaggle
Upload training_args.bin with git-lfs
Browse files- training_args.bin +3 -0
training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:3e32b2a478052e123b9c862f0c0c34c6fb1d7c937d03b560a66d6e5b16990166
|
| 3 |
+
size 3055
|