File size: 1,247 Bytes
d9e0a75
 
614cd1a
d9e0a75
614cd1a
d9e0a75
 
 
 
ed39965
614cd1a
ed39965
00f1f50
ed39965
d974702
2030f34
614cd1a
ed39965
614cd1a
ed39965
614cd1a
 
23ad6d7
614cd1a
 
23ad6d7
614cd1a
 
 
 
b22eea8
37275b7
 
fd8d93f
614cd1a
1d6f7dd
 
 
fdfd978
1d6f7dd
 
 
1e3a7ab
1d6f7dd
 
 
 
 
 
614cd1a
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
---
title: README
emoji: πŸš€
colorFrom: pink
colorTo: blue
sdk: static
pinned: false
---


**Name of the Project: News and Social Media Biases**

**Project Lead: Shaina Raza**

**Team Members:  Nifemi Bamgbose Mizanur Rahman, Shardul Ghuge, Farnaz Kohankhaki, Drai Paulen-Patterson, Yan Sidyakin, Veronica Chatrath**

**Location**: Canada

**Type of Project**: (Research Project / Application Development / Non-Profit Initiative)

**Established**: 2023

**Mission**: To detect and debias media biases using advanced NLP techniques

**Hugging Face Tools Used**:
- **Transformers Library**: To use pre-trained models like BERT, RoBERTa, Llama2 etc., for bias detection.
- **Datasets Library**: A collection of NLP datasets that can be useful in understanding and detecting biases in different media outlets.
- **Inference API**: For deploying the bias detection models in real-world applications.


**See package** https://pypi.org/project/UnBIAS/


**Contact Information**: [email protected]


## References

If you use our work, please cite this page:

```bibtex
@misc{raza2023newsmediabias,
  Author     = {Shaina Raza},
  title     = {News Media Bias},
  year      = {2023},
  url       = {https://huggingface.co/newsmediabias},
}
```