Instructions to use OliverHeine/bert-base-uncased_fold_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OliverHeine/bert-base-uncased_fold_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OliverHeine/bert-base-uncased_fold_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("OliverHeine/bert-base-uncased_fold_2") model = AutoModelForSequenceClassification.from_pretrained("OliverHeine/bert-base-uncased_fold_2") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 3
Browse files- model.safetensors +1 -1
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 438238176
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:9d01ca9fe4cc627dfad6689c5e3f715149dc347eaaf0b61f5152e34c29e9b28e
|
| 3 |
size 438238176
|