Instructions to use annedirkson/BERT_embeddings_ADR_normalization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use annedirkson/BERT_embeddings_ADR_normalization with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="annedirkson/BERT_embeddings_ADR_normalization")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("annedirkson/BERT_embeddings_ADR_normalization") model = AutoModel.from_pretrained("annedirkson/BERT_embeddings_ADR_normalization") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- .gitattributes +1 -0
- model.safetensors +3 -0
.gitattributes
CHANGED
|
@@ -16,3 +16,4 @@
|
|
| 16 |
*.pth filter=lfs diff=lfs merge=lfs -text
|
| 17 |
*.msgpack filter=lfs diff=lfs merge=lfs -text
|
| 18 |
*.msgpack filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 16 |
*.pth filter=lfs diff=lfs merge=lfs -text
|
| 17 |
*.msgpack filter=lfs diff=lfs merge=lfs -text
|
| 18 |
*.msgpack filter=lfs diff=lfs merge=lfs -text
|
| 19 |
+
model.safetensors filter=lfs diff=lfs merge=lfs -text
|
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:abb9eea5dd4845d8acb4d264d693b25d58881ed862ef2d39957ca40a2362bb1d
|
| 3 |
+
size 433267632
|