Instructions to use barthfab/drugprot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use barthfab/drugprot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="barthfab/drugprot")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("barthfab/drugprot") model = AutoModel.from_pretrained("barthfab/drugprot") - Notebooks
- Google Colab
- Kaggle
update pytorch_model.bin
#9
by barthfab - opened
- 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:f5eb83ce62fb122f933a42165517015d17cc44d29e23b55599fe7a2f2ac6df8d
|
| 3 |
+
size 433021681
|