News Summarizer
Length-conditioned abstractive summarization. Designed to distill lengthy Sinhala journalism into concise executive briefs or structured narratives without hallucinating facts outside the source article.
Paradigm
Abstractive
Generates new sentences
Formatting
Llama-3 Chat
Utilizes native chat templates
Length Control
3 Bands
Short, Medium, and Long targets
Adapter Version
v06
Current production deployment
Implementation Details
Length-Conditioned Prompts
Introduced in version v06, the summarizer now natively understands distinct length constraints natively. When an editor asks for a "short" summary, the model leverages its conditioned training to deliver an ultra-concise brief rather than truncating a longer output.
Supported Targets:
- Short: 2-3 sentence core briefs.
- Medium: Standard paragraph summary.
- Long: Multi-paragraph detailed synopsis retaining secondary facts.
Chat Template Utilization
While the Grammar, Headline, and Style tools rely on traditional Alpaca-style instruction prompts, the Summarizer is trained on the native Llama-3 Chat format (<|begin_of_text|><|start_header_id|>...).
This architectural divergence allows the model to better parse complex, multi-turn reasoning and handle document-scale texts with superior contextual retention.