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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
f832947
1
Parent(s): bd4ed3a
updated pytorch model for new concept dictionary
Browse files- pytorch_model.bin +1 -1
- tf_model.h5 +0 -3
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 433288887
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:75af94490c2391833cd56797ca40392ce132a277012ce5734df2d2b6a7aa4fa3
|
| 3 |
size 433288887
|
tf_model.h5
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:829fe1a1fd17b5e24b083705bf7a9a3969d092267415dcf950561ac9f416ffae
|
| 3 |
-
size 433503000
|
|
|
|
|
|
|
|
|
|
|
|