Instructions to use nlpaueb/sec-bert-shape with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlpaueb/sec-bert-shape with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nlpaueb/sec-bert-shape")# Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("nlpaueb/sec-bert-shape") model = AutoModelForPreTraining.from_pretrained("nlpaueb/sec-bert-shape") - Notebooks
- Google Colab
- Kaggle
Upload tf_model.h5 with git-lfs
Browse files- tf_model.h5 +3 -0
tf_model.h5
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:1cc3aad334c260d1b95d0b55e6d8f2394b2bd899574bd1b3f656bfbdef4ff8b1
|
| 3 |
+
size 532854280
|