Unsloth
Finetune LLMs 2x faster, 80% less memory
Unsloth launched on March 1, 2025 with 241 votes, #163 of 7,215 launches that month and more than 95% of that year's launches. The site was not reachable when checked in September 2026.
What it does
Unsloth could Finetune LLMs (DeepSeek, Llama 3, Mistral, Gemma, Qwen, Phi etc.) 2x faster with up to 80% less memory. Open-source, with free Colab notebooks. Now with reasoning capabilities!
Does a similar job
all alternatives →
80% faster, 50% less memory, 0% loss of accuracy Llama finetuning2023 · github.com · ▲385Hi HN! I'm just sharing a project I've been working on during the LLM Efficiency Challenge - you can now finetune Llama with QLoRA 5x faster than Huggingface's original implementation on your own local GPU. Some highlights: 1. Manual autograd engine - hand derived backprop steps. 2. QLoRA / LoRA 80% faster, 50% less memory. 3. All kernels written in OpenAI's Triton language. 4. 0% loss in accuracy - no approximation methods - all exact. 5. No change of hardware necessary. Supports NVIDIA GPUs since 2018+. CUDA 7.5+. 6. Flash Attention support via Xformers. 7. Supports 4bit and 16bit…
Finetune LLaMA-7B on commodity GPUs using your own text2023 · github.com · ▲449I've been playing around with https://github.com/zphang/minimal-llama/ and https://github.com/tloen/alpaca-lora/blob/main/finetune.py, and wanted to create a simple UI where you can just paste text, tweak the parameters, and finetune the model quickly using a modern GPU. To prepare the data, simply separate your text with two blank lines. There's an inference tab, so you can test how the tuned model behaves. This is my first foray into the world of LLM finetuning, Python, Torch, Transformers, LoRA, PEFT, and Gradio. Enjoy!
DeepSeek-R1-05282025 · huggingface.co · ▲218New open-source LLM that rivals o3 in coding & reasoning
finetune LLMs via the Finetuning Hub2023 · github.com · ▲80Hi HN community, I have been working on benchmarking publicly available LLMs these past couple of weeks. More precisely, I am interested on the finetuning piece since a lot of businesses are starting to entertain the idea of self-hosting LLMs trained on their proprietary data rather than relying on third party APIs. To this point, I am tracking the following 4 pillars of evaluation that businesses are typically look into: - Performance - Time to train an LLM - Cost to train an LLM - Inference (throughput / latency / cost per token) For each LLM, my aim is to benchmark them for…
Finetune Llama-3 2x faster in a Colab notebook2024 · colab.research.google.com · ▲45
Open-source fine-tuning in a Colab notebook2024 · colab.research.google.com · ▲5Posted before, but wanted to share if you want an open source alternative to OpenAI fine-tuning, give Unsloth a try! Phi 3.5 was just released, and is distilled from GPT4. Unsloth makes finetuning 2x faster, uses 70% less VRAM + has no accuracy degradations. We rewrite all backprop steps and reduce FLOPs and write everything in Triton (JIT low level CUDA). If you want to own the weights after fine-tuning, give Unsloth a spin! I have free Colabs and Kaggle notebooks as well at https://github.com/unslothai/unsloth
More ai this month
the category →
Paintings by AI models: programs run through a simulation of oil paint.
AI · 20d ago · stillwet.art
PixVerse R2▲381A real-time world model you can explore and change
AI · 28d ago · world.pixverse.video
Source: Product Hunt launch ↗
Launched alongside, March 2025
the whole month →
Mimic Human Research & Save Findings in AI Knowledge Base
AI · 2025 · sider.ai
