Adapting Safe-for-Work Classifier for Malaysian Language Text: Enhancing
  Alignment in LLM-Ops Framework
As large language models (LLMs) become increasingly integrated into
operational workflows (LLM-Ops), there is a pressing need for effective
guardrails to ensure safe and aligned interactions, including the ability to
detect potentially unsafe or inappropriate content across languages. However,
existing safe-for-work classifiers are primarily focused on English text. To
address this gap for the Malaysian language, we present a novel safe-for-work
text classifier tailored specifically for Malaysian language content. By
curating and annotating a first-of-its-kind dataset of Malaysian text spanning
multiple content categories, we trained a classification model capable of
identifying potentially unsafe material using state-of-the-art natural language
processing techniques. This work represents an important step in enabling safer
interactions and content filtering to mitigate potential risks and ensure
responsible deployment of LLMs. To maximize accessibility and promote further
research towards enhancing alignment in LLM-Ops for the Malaysian context, the
model is publicly released at
https://huggingface.co/malaysia-ai/malaysian-sfw-classifier.
66a9c5650ab13bd9ed49c692
Aisyah Razak
extracted_confirmed
2024-07-31T06:38:12.054Z
61f3bfa371eee6f88ca0cef7
https://cdn-avatars.huggingface.co/v1/production/uploads/61f3bfa371eee6f88ca0cef7/UYzexDtBWqfRo_dbYs6Q5.jpeg
aisyah
user
aisyahhrazak
66a9c5650ab13bd9ed49c693
Ariff Nazhan
extracted_pending
2024-07-31T05:02:30.293Z
64cef95b995a0b5d594c68da
https://cdn-avatars.huggingface.co/v1/production/uploads/64cef95b995a0b5d594c68da/vhz8omT0W8B-JERbETJrB.jpeg
Ariff Nazhan
user
nazhan
66a9c5650ab13bd9ed49c694
Kamarul Adha
extracted_pending
2024-07-31T05:02:30.293Z
6435fdee76dbfd731bcde0eb
/avatars/66d930bb4e3b96abd449b6173675728e.svg
Kamarul Adha
user
Hiraishin
66a9c5650ab13bd9ed49c695
Wan Adzhar Faiq Adzlan
extracted_confirmed
2024-07-31T10:25:41.063Z
64ce21ecd2a781d3f0da326a
https://cdn-avatars.huggingface.co/v1/production/uploads/noauth/dt5WZlyO-axA9QQij1zUh.jpeg
Faiq Adzlan
user
wanadzhar913
66a9c5650ab13bd9ed49c696
Mas Aisyah Ahmad
extracted_pending
2024-07-31T05:02:30.293Z
665891a41f6b7b30facd23a4
/avatars/e6f2b654082308a0c18a3b4f10bf1589.svg
neko
user
nekoketew
66a9c5650ab13bd9ed49c697
Ammar Azman
admin_assigned
2024-07-31T08:32:58.296Z
64cf470386e19d5db168b6ce
https://cdn-avatars.huggingface.co/v1/production/uploads/noauth/Z9jZODTP5SlKwb3zqs96u.jpeg
Ammar Azman
user
ammarxix
Adapting Safe-for-Work Classifier for Malaysian Language Text: Enhancing
  Alignment in LLM-Ops Framework
As large language models (LLMs) become increasingly integrated into
operational workflows (LLM-Ops), there is a pressing need for effective
guardrails to ensure safe and aligned interactions, including the ability to
detect potentially unsafe or inappropriate content across languages. However,
existing safe-for-work classifiers are primarily focused on English text. To
address this gap for the Malaysian language, we present a novel safe-for-work
text classifier tailored specifically for Malaysian language content. By
curating and annotating a first-of-its-kind dataset of Malaysian text spanning
multiple content categories, we trained a classification model capable of
identifying potentially unsafe material using state-of-the-art natural language
processing techniques. This work represents an important step in enabling safer
interactions and content filtering to mitigate potential risks and ensure
responsible deployment of LLMs. To maximize accessibility and promote further
research towards enhancing alignment in LLM-Ops for the Malaysian context, the
model is publicly released at
https://huggingface.co/malaysia-ai/malaysian-sfw-classifier.
A novel safe-for-work text classifier for Malaysian language content is developed using a curated dataset of Malaysian text and state-of-the-art natural language processing techniques, enhancing alignment in LLM-Ops.
natural language processing large language models LLM-Ops safe-for-work classifiers text classification dataset curation text annotation