Instructions to use OpenSemShift/bert-c1-en-de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenSemShift/bert-c1-en-de with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="OpenSemShift/bert-c1-en-de")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("OpenSemShift/bert-c1-en-de") model = AutoModelForMaskedLM.from_pretrained("OpenSemShift/bert-c1-en-de") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:7eafc14e14a906887eda38ef15bd710f57e4384b1e16386cdf2e8ceff6af2477
|
| 3 |
+
size 714284492
|