Instructions to use EhimeNLP/AcademicBART with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EhimeNLP/AcademicBART with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="EhimeNLP/AcademicBART")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("EhimeNLP/AcademicBART") model = AutoModel.from_pretrained("EhimeNLP/AcademicBART") - Notebooks
- Google Colab
- Kaggle
Delete pytorch_model.bin
Browse files- pytorch_model.bin +0 -3
pytorch_model.bin
DELETED
|
@@ -1,3 +0,0 @@
|
|
| 1 |
-
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:f5eefd5066949e97f4f69142f8bbbb7242a2f42290ee97ce177d373950ffa0bc
|
| 3 |
-
size 501704571
|
|
|
|
|
|
|
|
|
|
|
|