Instructions to use HeTree/HeConEspc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HeTree/HeConEspc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HeTree/HeConEspc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HeTree/HeConEspc") model = AutoModelForSequenceClassification.from_pretrained("HeTree/HeConEspc") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -56,7 +56,7 @@ tokenized_data = raw_dataset_window.map(tokenize_function, batched=True)
|
|
| 56 |
|
| 57 |
### Citing
|
| 58 |
|
| 59 |
-
If you use HeConEspc in your research, please cite [
|
| 60 |
```
|
| 61 |
@article{shalumov2024mevaker,
|
| 62 |
title={Mevaker: Conclusion Extraction and Allocation Resources for the Hebrew Language},
|
|
|
|
| 56 |
|
| 57 |
### Citing
|
| 58 |
|
| 59 |
+
If you use HeConEspc in your research, please cite [Mevaker: Conclusion Extraction and Allocation Resources for the Hebrew Language](https://arxiv.org/abs/2403.09719).
|
| 60 |
```
|
| 61 |
@article{shalumov2024mevaker,
|
| 62 |
title={Mevaker: Conclusion Extraction and Allocation Resources for the Hebrew Language},
|