Update README.md
Browse files
README.md
CHANGED
@@ -9,7 +9,9 @@ widget:
|
|
9 |
## Model description
|
10 |
**CAMeLBERT-DA SA Model** is a Sentiment Analysis (SA) model that was built by fine-tuning the [CAMeLBERT Dialectal Arabic (DA)](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-da/) model.
|
11 |
For the fine-tuning, we used the [ASTD](https://aclanthology.org/D15-1299.pdf), [ArSAS](http://lrec-conf.org/workshops/lrec2018/W30/pdf/22_W30.pdf), and [SemEval](https://aclanthology.org/S17-2088.pdf) datasets.
|
12 |
-
Our fine-tuning procedure and the hyperparameters we used can be found in our paper *"[The Interplay of Variant, Size, and Task Type in Arabic Pre-trained Language Models](https://arxiv.org/abs/2103.06678)."
|
|
|
|
|
13 |
## Intended uses
|
14 |
You can use the CAMeLBERT-DA SA model directly as part of our [CAMeL Tools](https://github.com/CAMeL-Lab/camel_tools) SA component (*recommended*) or as part of the transformers pipeline.
|
15 |
#### How to use
|
@@ -24,13 +26,15 @@ To use the model with the [CAMeL Tools](https://github.com/CAMeL-Lab/camel_tools
|
|
24 |
You can also use the SA model directly with a transformers pipeline:
|
25 |
```python
|
26 |
>>> from transformers import pipeline
|
27 |
-
>>> sa = pipeline('
|
28 |
>>> sentences = ['أنا بخير', 'أنا لست بخير']
|
29 |
>>> sa(sentences)
|
30 |
[{'label': 'positive', 'score': 0.9616648554801941},
|
31 |
{'label': 'negative', 'score': 0.9779177904129028}]
|
32 |
```
|
33 |
-
*Note*: to download our models, you would need `transformers>=3.5.0`.
|
|
|
|
|
34 |
## Citation
|
35 |
```bibtex
|
36 |
@inproceedings{inoue-etal-2021-interplay,
|
|
|
9 |
## Model description
|
10 |
**CAMeLBERT-DA SA Model** is a Sentiment Analysis (SA) model that was built by fine-tuning the [CAMeLBERT Dialectal Arabic (DA)](https://huggingface.co/CAMeL-Lab/bert-base-arabic-camelbert-da/) model.
|
11 |
For the fine-tuning, we used the [ASTD](https://aclanthology.org/D15-1299.pdf), [ArSAS](http://lrec-conf.org/workshops/lrec2018/W30/pdf/22_W30.pdf), and [SemEval](https://aclanthology.org/S17-2088.pdf) datasets.
|
12 |
+
Our fine-tuning procedure and the hyperparameters we used can be found in our paper *"[The Interplay of Variant, Size, and Task Type in Arabic Pre-trained Language Models](https://arxiv.org/abs/2103.06678)."
|
13 |
+
* Our fine-tuning code can be found [here](https://github.com/CAMeL-Lab/CAMeLBERT).
|
14 |
+
|
15 |
## Intended uses
|
16 |
You can use the CAMeLBERT-DA SA model directly as part of our [CAMeL Tools](https://github.com/CAMeL-Lab/camel_tools) SA component (*recommended*) or as part of the transformers pipeline.
|
17 |
#### How to use
|
|
|
26 |
You can also use the SA model directly with a transformers pipeline:
|
27 |
```python
|
28 |
>>> from transformers import pipeline
|
29 |
+
>>> sa = pipeline('text-classification', model='CAMeL-Lab/bert-base-arabic-camelbert-da-sentiment')
|
30 |
>>> sentences = ['أنا بخير', 'أنا لست بخير']
|
31 |
>>> sa(sentences)
|
32 |
[{'label': 'positive', 'score': 0.9616648554801941},
|
33 |
{'label': 'negative', 'score': 0.9779177904129028}]
|
34 |
```
|
35 |
+
*Note*: to download our models, you would need `transformers>=3.5.0`.
|
36 |
+
Otherwise, you could download the models manually.
|
37 |
+
|
38 |
## Citation
|
39 |
```bibtex
|
40 |
@inproceedings{inoue-etal-2021-interplay,
|