Instructions to use anhuu/argument_classification_stance_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anhuu/argument_classification_stance_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="anhuu/argument_classification_stance_bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("anhuu/argument_classification_stance_bert") model = AutoModelForSequenceClassification.from_pretrained("anhuu/argument_classification_stance_bert") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 5
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 438008370
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d9aa2514ff34afbcaf870e4e5a1b39da5923331d92814546fed53fb7ebb6461d
|
| 3 |
size 438008370
|
runs/Nov18_14-01-16_4f7fb582062b/events.out.tfevents.1700316079.4f7fb582062b.353.4
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 sha256:4f3a104e5ee5a480d0f55aca06de10ff981a72464e6af7084c5c0ec6d3d9ac31
|
| 3 |
+
size 4060
|