Detect Romanized Sinhala hate speech using XLM-RoBERTa.
Project description
🇱🇰 Romanized Sinhala Hate Speech Detection
This project aims to detect hate speech in Romanized Sinhala text using transformer-based deep learning models (e.g., XLM-RoBERTa). It includes both the model training pipeline and inference (prediction) functionality.
🔡 Supported Input
The model expects Romanized Sinhala text, such as:
"umbalata lokuwatma pissu""mokada oya karanne"
The input is automatically tokenized and passed to the model for classification.
🧪 Model Output
0→ Not Hate Speech1→ Hate Speech
📜 License
This project is for academic and research use. Please contact the author before using it for commercial purposes.
✍️ Author
Sakun Chamikara
MSc Research Project – Romanized Sinhala Hate Speech Detection
Sri Lanka
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file romsi_hate_speech-1.0.0.tar.gz.
File metadata
- Download URL: romsi_hate_speech-1.0.0.tar.gz
- Upload date:
- Size: 3.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.10.11
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
e94dd93827e9c4dfc23d1eaf65ba5e53ed30df619507697bf58d5239f8b37dbe
|
|
| MD5 |
4d4cd43c337b2a05681eb76e64c085b3
|
|
| BLAKE2b-256 |
19008887c6586224434519bb64a3d2cd57d8b0e355e9f42672c7977b9eef0c45
|
File details
Details for the file romsi_hate_speech-1.0.0-py3-none-any.whl.
File metadata
- Download URL: romsi_hate_speech-1.0.0-py3-none-any.whl
- Upload date:
- Size: 5.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.10.11
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
fd6ab6a8b2e4d7dd87f937f5efa93cb8a0b33a0035162ea86dcf4863699e3cb7
|
|
| MD5 |
ad770933009cfe4549fb31cc33056724
|
|
| BLAKE2b-256 |
c0bc5c52e2706b2f3256de75e44ba757c3f5ae29e62cc38c21e937ed9d0c1fe1
|