README
TikGuard Backend - AI
This is a Django backend to use with the NextJS frontend to interact with various AI models.
Usage
$ python3 -m venv venv/
Windows
$ .\venv\Scripts\python.exe -m pip install -r requirements.txt
$ .\venv\Scripts\python.exe .\manage.py runserver
Linux/Mac
$ ./venv/bin/python -m pip install -r requirements.txt
$ ./venv/bin/python ./manage.py runserver
Endpoints
| Endpoint | Purpose | Method | Data | Response |
|---|---|---|---|---|
/api/list_models | To list the current models accessible via the API | GET | N/A | {"models":[<list of model identifiers>]} |
/api/use_model | To utilise an accesible model | POST | {"model":"model-name-from-list","data":"text-data-to-check"} | {"parsed_response": {"ishateful": <bool>}, "raw_response": "<raw model response>"} |
Author
Made by sealldeveloper / sealldev
Models
- facebook/roberta-hate-speech-dynabench-r4-target
- Hate-speech-CNERG/english-abusive-MuRIL
- IMSyPP/hate_speech_en
Papers
- Learning from the Worst: Dynamically Generated Datasets to Improve Online Hate Detection by Bertie Vidgen and Tristan Thrush and Zeerak Waseem and Douwe Kiela (2021)
- Data Bootstrapping Approaches to Improve Low Resource Abusive Language Detection for Indic Languages by Das, Mithun and Banerjee, Somnath and Mukherjee, Animesh (2022)
- Kralj Novak, P., Scantamburlo, T., Pelicon, A., Cinelli, M., Mozetič, I., & Zollo, F. (2022, July). Handling disagreement in hate speech modelling. In International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (pp. 681-695). Cham: Springer International Publishing. https://link.springer.com/chapter/10.1007/978-3-031-08974-9_54
Contributors
minhvyha
1 commits
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Languages
Python
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README
TikGuard Backend - AI
This is a Django backend to use with the NextJS frontend to interact with various AI models.
Usage
$ python3 -m venv venv/
Windows
$ .\venv\Scripts\python.exe -m pip install -r requirements.txt
$ .\venv\Scripts\python.exe .\manage.py runserver
Linux/Mac
$ ./venv/bin/python -m pip install -r requirements.txt
$ ./venv/bin/python ./manage.py runserver
Endpoints
| Endpoint | Purpose | Method | Data | Response |
|---|---|---|---|---|
/api/list_models | To list the current models accessible via the API | GET | N/A | {"models":[<list of model identifiers>]} |
/api/use_model | To utilise an accesible model | POST | {"model":"model-name-from-list","data":"text-data-to-check"} | {"parsed_response": {"ishateful": <bool>}, "raw_response": "<raw model response>"} |
Author
Made by sealldeveloper / sealldev
Models
- facebook/roberta-hate-speech-dynabench-r4-target
- Hate-speech-CNERG/english-abusive-MuRIL
- IMSyPP/hate_speech_en
Papers
- Learning from the Worst: Dynamically Generated Datasets to Improve Online Hate Detection by Bertie Vidgen and Tristan Thrush and Zeerak Waseem and Douwe Kiela (2021)
- Data Bootstrapping Approaches to Improve Low Resource Abusive Language Detection for Indic Languages by Das, Mithun and Banerjee, Somnath and Mukherjee, Animesh (2022)
- Kralj Novak, P., Scantamburlo, T., Pelicon, A., Cinelli, M., Mozetič, I., & Zollo, F. (2022, July). Handling disagreement in hate speech modelling. In International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (pp. 681-695). Cham: Springer International Publishing. https://link.springer.com/chapter/10.1007/978-3-031-08974-9_54
Similar repos
Contributors
minhvyha
1 commits
Languages
Python
100.0%