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
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:c3481c436d3568ea47041e51b6ad80b70a3657fcccffc1c21282da2b80fe1acd
|
| 3 |
+
size 501652064
|