Instructions to use Milanmg/bert-base-multilingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Milanmg/bert-base-multilingual with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Milanmg/bert-base-multilingual")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Milanmg/bert-base-multilingual") model = AutoModelForMaskedLM.from_pretrained("Milanmg/bert-base-multilingual") - 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 sha256:8c6fe40eebcaffac5051e6dddc93318faedfc74ed17b0de0c2512a3158f77ce5
|
| 3 |
+
size 1083389348
|