tf2-12b-gguf

🦊 klusai/tf2-12b — LoRA-tuned EN→RO Translator (Fables) — GGUF build

klusai/tf2-12b is a Gemma 3 12B (Instruct) based translator, fine-tuned with LoRA on 15,000 English→Romanian fable pairs (synthetic, generated with GPT-o3). This repository distributes the merged weights in GGUF format for fast inference with llama.cpp-compatible runtimes.

Focus: faithful, fluent EN→RO translation of short moral fables, preserving tone, structure, and morals (with proper Romanian diacritics).

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✨ Highlights

• Task: EN→RO translation for narrative prose (fables).
• Training: Parameter-efficient LoRA; adapters merged into base and exported to GGUF.
• Data: 15k synthetic pairs generated by GPT-o3.
• Format: GGUF (llama.cpp). Multiple quantizations may be provided (e.g. Q5_K_M, F16).

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🧱 I/O Contract

• Input: English fable paragraph(s) + concise instruction to translate to Romanian.
• Output: Romanian translation that is faithful, fluent, and keeps the moral explicit.

Prompting tip: “Translate to Romanian with proper diacritics. Preserve meaning, tone, and moral. Avoid adding content.”

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🧪 Training Summary

• Base model: Gemma 3 12B (Instruct)
• Method: LoRA fine-tuning; adapters merged for deployment
• Dataset: 15k EN→RO fable translations (GPT-o3 generated)

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✅ Intended Use

• Education/NLP demos, EN→RO machine translation of narrative content, style-preserving localization.

⚠️ Limitations

• Tuned on fables; may underperform on legal/medical/colloquial domains.
• Synthetic data can carry stylistic biases or occasional literalism.
• Always add human review for production use.

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🔑 Licensing

• This GGUF build: MIT
• Use must also comply with the Gemma base model license/terms.

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📝 Changelog

• v1.0 (GGUF) — Initial public GGUF release (LoRA-merged). Multiple quantizations provided (e.g., Q5_K_M).