Instructions to use kanishka/GlossBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kanishka/GlossBERT with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("kanishka/GlossBERT", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Kanishka Misra commited on
Commit ·
542ccb8
1
Parent(s): 5e68839
Added code to load the model
Browse files
README.md
CHANGED
|
@@ -13,6 +13,17 @@ A BERT-based model fine-tuned on SemCor 3.0 to perform word-sense-disambiguation
|
|
| 13 |
|
| 14 |
Disclaimer: This model was built and trained by a group of researchers different than the repository's author. The original model code can be found on github: https://github.com/HSLCY/GlossBERT
|
| 15 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 16 |
## Citation
|
| 17 |
|
| 18 |
If you use this model in any of your projects, please cite the original authors using the following bibtex:
|
|
|
|
| 13 |
|
| 14 |
Disclaimer: This model was built and trained by a group of researchers different than the repository's author. The original model code can be found on github: https://github.com/HSLCY/GlossBERT
|
| 15 |
|
| 16 |
+
## Usage
|
| 17 |
+
|
| 18 |
+
The following code loads GlossBERT:
|
| 19 |
+
|
| 20 |
+
```py
|
| 21 |
+
from transformers import AutoTokenizer, BertForSequenceClassification
|
| 22 |
+
|
| 23 |
+
tokenizer = AutoTokenizer.from_pretrained('kanishka/GlossBERT')
|
| 24 |
+
model = BertForSequenceClassification.from_pretrained('kanishka/GlossBERT')
|
| 25 |
+
```
|
| 26 |
+
|
| 27 |
## Citation
|
| 28 |
|
| 29 |
If you use this model in any of your projects, please cite the original authors using the following bibtex:
|