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Check out the documentation for more information.
license: gemma language:
- ko
- en pipeline_tag: text-generation tags:
- korean
- gemma
- roleplay
- comment-generation
- diary
Gemma-3-1B Korean Novel Commenter
A lightweight conversational model designed to write comments on usersโ diary or SNS-style posts.
Instead of general chatting, the model is specialized for reaction writing: reading a personal text and replying as if a real person left a comment under the post.
This model is used in the mobile app:
https://play.google.com/store/apps/details?id=com.chensi.offgram&hl=ko
Provided Files
Currently recommended:
comment_270m_260204.ggufโ very fast, low resource inferencecomment_1b_260203.ggufโ higher quality responses
The 270M version is intended for on-device usage. The 1B version produces more natural emotional reactions but still keeps low compute requirements.
What the Model Does
The model reads a diary entry or SNS-like post and generates a human-like reaction comment.
Typical outputs include:
- empathy
- encouragement
- emotional reaction
- casual conversation-style replies
It is not a general knowledge assistant and will perform poorly on factual Q&A tasks.
Prompt Format
System
๋๋ SNS ์ผ๊ธฐ์ ๋๊ธ์ ๋ค๋ ์ฌ๋์ด๋ค.
User
[COMMENTER_PROFILE]$ageString ${character.gender}
[COMMENTER_STYLE]${character.speechStyle}
[COMMENT_LENGTH]${character.reactionLength}
[LANG]$lang
[DIARY]$diaryContent
[COMMENT]
Prompt Field Explanation
COMMENTER_PROFILE
- Social age group expression (e.g., early 20s, mid-30s, late-40s)
- Gender: male / female
COMMENTER_STYLE
Defines personality and speaking style based on ai_comment.json.
Examples:
- polite and considerate
- warm empathy
- casual teenage friendliness
- calm encouragement
COMMENT_LENGTH
Controls approximate response length.
Values typically: 1, 1~2, 1~3 (roughly number of sentences)
LANG Final output language. Currently supported:
koen(more planned)
DIARY Actual user diary text written inside the app.
Training Characteristics
- Base: Gemma family small model
- Task: emotional reaction generation
- Data: primarily empathy-focused conversational text
- Optimized for: supportive responses rather than diverse knowledge
Because of the small model size (especially 270M), responses may be simple and sometimes repetitive. The model prioritizes emotional appropriateness over linguistic variety.
Continuous updates are planned to improve diversity and naturalness.
Limitations
- Limited factual accuracy
- Repetition in long conversations
- Weak reasoning capability
- Not suitable for coding or academic Q&A
This model is intended for social interaction simulation, not an information assistant.
Intended Use
- diary apps
- SNS companion systems
- roleplay interaction
- emotional feedback systems
- character comment generation
Notes
The model is designed to respond kindly and supportively to personal writing. It may over-empathize or avoid negative reactions due to training bias.
License
gemma
Citation
If you use this model in research or applications, please reference the Hugging Face repository.
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