Developer fine-tunes GPT OSS 20B on consumer GPU using Unsloth

A developer has detailed a process for fine-tuning the GPT OSS 20B model using Unsloth on a single consumer GPU, requiring approximately 14 GB of VRAM. The fine-tuned model, optimized for STEM reasoning, is available in three formats: a LoRA adapter, a merged 16-bit model, and GGUF files. A critical aspect highlighted is the necessity of using OpenAI's Harmony chat template, including specific stop tokens like '<|return|>', to ensure correct output and prevent issues such as gibberish or unending generation when running the model in platforms like Ollama. AI

IMPACT Enables running and fine-tuning larger models on consumer hardware, democratizing access to advanced AI capabilities.

RANK_REASON The article describes fine-tuning an existing open-source model using specific tools and techniques, and how to deploy it, rather than a new model release from a frontier lab.

Read on dev.to — LLM tag →

• GGUF
• GPT OSS 20B
• Harmony
• llama.cpp
• LM Studio
• LoRA
• Ollama
• QLoRA
• transformers
• Unsloth
• vLLM

• model release
• product

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