Instructions to use deprem-ml/name_anonymization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deprem-ml/name_anonymization with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="deprem-ml/name_anonymization")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("deprem-ml/name_anonymization") model = AutoModelForTokenClassification.from_pretrained("deprem-ml/name_anonymization") - Notebooks
- Google Colab
- Kaggle
Upload BertForTokenClassification
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 440186673
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:063771ed088e2fc2c74a50b4d3fb6c0cf893308cd810a56e260d04b72ba3f4d1
|
| 3 |
size 440186673
|