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 pytorch_model.bin with git-lfs
Browse files- pytorch_model.bin +3 -0
pytorch_model.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:3496a508a9a3511c8a55e4d0e6f471c70c68c2a8c4784b3b2b5dc16ffb87d238
|
| 3 |
+
size 714314041
|