Researchers released a benchmark for Arabic-Russian scientific translation, including a 27,000-sentence parallel corpus and fine-tuned multilingual models. The Qwen2.5-7B model achieved BLEU 23.15, ou…
A developer details practical QLoRA fine-tuning using Axolotl and Unsloth, explaining how parameter-efficient methods like LoRA and QLoRA enable training multi-billion parameter models on a single con…
LoRA (Low-Rank Adaptation) and QLoRA have become widely adopted methods for efficiently fine-tuning large language models with a fraction of the parameters, solving the problem of massive GPU requirem…
Developer Torgeir Helgevold fine-tuned a 600-million-parameter local LLM (Qwen 3:0.6B) to classify household questions into metadata categories, achieving 92% accuracy on a test set—up from 10% with p…
A developer fine-tuned a tiny 0.6B-parameter Qwen 3 model to categorize household questions into metadata categories like pool, car, and HVAC. The baseline model achieved only 10% accuracy via prompti…
A developer fine-tuned Qwen2.5-7B on a 16GB T4 GPU using QLoRA, quantizing the frozen base model to 4-bit NF4 to reduce memory footprint from 15GB to 5.44GB. The technique enables training large langu…
A developer fully fine-tuned a 270M-parameter Gemma 3 model on a laptop using the Banking77 dataset, achieving ~96% accuracy on intent classification. The project used full fine-tuning with loss maski…
Nick Creighton, a developer and host of the *Build Log* podcast, has published a practical comparison of full-model fine-tuning, LoRA, and QLoRA for adapting large language models in 2024. The guide d…
A self-taught student successfully fine-tuned the open-source Qwen 2.5-7B language model into a Discord bot named Monika, using 687 in-game dialogues and QLoRA 4-bit compression on Google Colab's free…
Google announced the Google Colab Command-Line Interface (CLI), a tool that connects local terminals to remote Colab runtimes for zero-friction execution by developers and AI agents. The CLI enables u…
A developer's analysis of LLM fine-tuning versus retrieval-augmented generation (RAG) finds that roughly 70% of production LLM problems are solved by better prompting or RAG, with fine-tuning reserved…
Researchers have developed EURO-5K, a new dataset of sentence-level reporting obligations from 136 EU legislative acts, to improve automated extraction of regulatory requirements. Benchmarking discrim…
Liquid AI's LFM2 model can be fine-tuned using QLoRA and DPO in a complete open-source workflow on Google Colab. The process loads the base LFM2 checkpoint with 4-bit quantization, trains a lightweigh…
Researchers in Japan fine-tuned the LLaVA-1.5-7B vision-language model on up to 4,000 bridge damage images to automate damage assessment and repair priority scoring, addressing significant inter-rater…
The author successfully fine-tuned a 1.1 billion parameter TinyLlama model using QLoRA on consumer hardware, training only 0.2% of the model's parameters via low-rank adapter matrices. The project inv…