Sarvix Multilingual 1
Fine-tuned from Qwen2.5-1.5B-Instruct using LoRA (r=16, alpha=32) on 768 assert-only examples across 13 languages. The model takes a vague, ambiguous, or emotionally loaded message and confidently restates what the sender most likely meant — without asking any questions. It always responds in the same language as the input.
Behavior
- Input: a short, vague, or emotionally loaded chat message
- Output: a confident restatement of the likely intended meaning
- Never asks questions — always commits to an interpretation
- Responds in the same language as the input
Training
- Base: Qwen/Qwen2.5-1.5B-Instruct
- Method: LoRA (target modules: q_proj, k_proj, v_proj, o_proj)
- Epochs: 3
- Dataset: 768 assert-only examples across 13 languages
- Languages: English, Spanish, French, German, Portuguese, Japanese, Arabic, Hindi, Swahili, Italian, Russian, Korean, Chinese (Mandarin)
Known limitations
- Swahili, Hindi, and Korean may produce less fluent output due to lower training coverage compared to the other languages.