Instructions to use anahitapld/dbd_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anahitapld/dbd_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="anahitapld/dbd_bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("anahitapld/dbd_bert") model = AutoModelForSequenceClassification.from_pretrained("anahitapld/dbd_bert") - Notebooks
- Google Colab
- Kaggle
Commit ·
51fe60b
1
Parent(s): d88162f
- pytorch_model.bin +3 -0
pytorch_model.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:3097704520787e26e2768e61dfb76884a414620f9dcbdcb48be41dd4b106f614
|
| 3 |
+
size 433318253
|