Instructions to use d4data/bias-detection-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use d4data/bias-detection-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="d4data/bias-detection-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("d4data/bias-detection-model") model = AutoModelForSequenceClassification.from_pretrained("d4data/bias-detection-model") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -40,6 +40,6 @@ classifier("The irony, of course, is that the exhibit that invites people to thr
|
|
| 40 |
```
|
| 41 |
|
| 42 |
## Author
|
| 43 |
-
This model is part of the Research topic "Bias and Fairness in AI" conducted by Deepak John Reji, Shaina Raza. If you use this work (code, model or dataset), please
|
| 44 |
-
> Bias & Fairness in AI, (2022), GitHub repository, <https://github.com/dreji18/Fairness-in-AI
|
| 45 |
|
|
|
|
| 40 |
```
|
| 41 |
|
| 42 |
## Author
|
| 43 |
+
This model is part of the Research topic "Bias and Fairness in AI" conducted by Deepak John Reji, Shaina Raza. If you use this work (code, model or dataset), please star at:
|
| 44 |
+
> Bias & Fairness in AI, (2022), GitHub repository, <https://github.com/dreji18/Fairness-in-AI>
|
| 45 |
|