🦙 Liyama-3B
Liyama-3B is a fine-tuned version of Meta’s LLaMA-3B (3.2) model, built to understand and respond fluently in Tagalog. It was trained on the AnoNa dataset over 3 epochs, aiming for natural, context-aware instruction-following in Filipino.
🔤 Origin of the Name
The name Liyama is a Tagalified version of llama, reflecting both its LLaMA base and its Tagalog-focused language capabilities. It mirrors how Filipino often adapts foreign terms into familiar, phonetic forms—like camera → kamera, lion → leon, and now, llama → liyama.
🧠 Training Data: The AnoNa Dataset
Liyama-3B was trained solely on response completions from the AnoNa dataset — a self-instruct corpus generated using Gemini 1.5 and 2.0.
Inspired by SimpleQnA, the dataset contains short, helpful instruction-response pairs. But AnoNa introduces several improvements:
- ✅ Less English, More Tagalog prompts
- ✅ Less IFEVAL-style formatting
- ✅ No overuse of modifiers in instructions
- ✅ Balanced task types to avoid dominant categories
- ✅ Complex tasks favored (65% complex / 35% simple)
- ✅ Reduced sycophancy and generic praise
- ✅ Improved follow-up handling
- ✅ AI self-intro appears only when relevant
- ✅ Implicit chain-of-thought reasoning, not labeled
- ✅ Extra task types added to increase variety
This focus creates a model that's practical, straightforward, and tuned for realistic conversational use in Filipino, without excessive formatting or irrelevant disclaimers.
🗣️ Use Case
Liyama-3B is ideal for:
- Answering questions in Tagalog
- Writing essays, reflections, and letters in Filipino
- Following natural instructions, even when mixed with English
- Chat-based tasks where fluency and tone matter
- Educational or community apps centered around local language use
📦 Model Details
| Feature | Value |
|---|
| Base Model | LLaMA-3B v3.2 |
| Fine-tuned Dataset | AnoNa |
| Epochs | 3 |
| Language Focus | Tagalog (with some English) |
| Prompt Format | Responses only |
Liyama-3B is part of a broader effort to create open, practical Filipino-language models for real use—not just benchmarks. Expect follow-ups tuned for multi-turn chat, reasoning, and creative tasks.
