Instructions to use UdS-LSV/smole-bart with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UdS-LSV/smole-bart with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("UdS-LSV/smole-bart") model = AutoModelForSeq2SeqLM.from_pretrained("UdS-LSV/smole-bart") - Notebooks
- Google Colab
- Kaggle
Commit ·
c8d4a44
1
Parent(s): 75bcb93
Update README.md
Browse files
README.md
CHANGED
|
@@ -25,3 +25,4 @@ Introduces contrastive learning alongside multi-task regression, and masked lang
|
|
| 25 |
- Pretrain BART model with Denoising objective on noised Guacamol dataset
|
| 26 |
|
| 27 |
|
|
|
|
|
|
| 25 |
- Pretrain BART model with Denoising objective on noised Guacamol dataset
|
| 26 |
|
| 27 |
|
| 28 |
+
Fore more details please see our [github repository](https://github.com/uds-lsv/enumeration-aware-molecule-transformers).
|