Instructions to use ixa-ehu/berteus-base-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ixa-ehu/berteus-base-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ixa-ehu/berteus-base-cased")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ixa-ehu/berteus-base-cased") model = AutoModel.from_pretrained("ixa-ehu/berteus-base-cased") - Notebooks
- Google Colab
- Kaggle
Update pytorch_model.bin
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:e0bf523551be9176a9bad3d3674b14ac833a1be908a5b53da844349e21f27283
|
| 3 |
+
size 498112140
|