Created a 309K Turkish Python Instruction Dataset to fine-tune custom coding models for Ollama / llama.cpp

Hey Ollama community, If you are planning to fine-tune and build your own local Turkish coding models (using Unsloth / LoRA to export to GGUF and run in Ollama via custom Modelfiles), I've open-sourced a massive 309K+ instruction dataset. 🔗 Hugging Face Hub: https://huggingface.co/datasets/bysismo/Turkish-Python-instruction-300k --- ### 🛠️ Why this helps local Ollama models: Running generic translated models locally often yields broken syntax and hallucinations in non-English coding tasks. This dataset is strictly structured and split into 5 Golden Token Tiers (≤96T, ≤186T, ≤286T, ≤386T, ≤512T) to keep KV cache memory predictable and training loss optimal on consumer GPUs. - Coverage: Core Python, Advanced OOP (C3/MRO, Metaclasses), System/Shell, and Database logic. - Formats: Available as ready-to-train JSONL partitions and a 1-click 277MB master file (Turkish-Python-instruction.jsonl). Once we fine-tune the first Qwen2.5-Coder / Llama-3 checkpoints on this dataset, I will also publish the quantized GGUF files and ready-to-run Ollama Modelfiles! Feedback and model requests are welcome! submitted by /u/bysismo [link] [comments]

Source: r/ollama | 2026-08-16