Ask HN: Most efficient way to fine-tune an LLM in 2024?

1. unsloth

   1 34 65,904 10.0 Python

   Unsloth Studio is a web UI for training and running open models like Gemma 4, Qwen3.6, DeepSeek, gpt-oss locally.

   

   Gemma 7b is 2.4x faster than HF + FA2.

   Check out https://github.com/unslothai/unsloth for full benchmarks!

2. SaaSHub

   www.saashub.com featured

   SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

   

3. axolotl

   2 39 12,003 9.7 Python

   Go ahead and axolotl questions

   

   The approach I see used is axolotl with QLoRA using cloud GPUs which can be quite cheap.

   https://github.com/OpenAccess-AI-Collective/axolotl

4. dspy

   3 58 34,875 9.7 Python

   DSPy: The framework for programming—not prompting—language models

   

5. skypilot

   4 43 10,066 9.9 Python

   Run, manage, and scale AI workloads on any AI infrastructure. Use one system to access & manage all AI compute (Kubernetes, Slurm, 20+ clouds, on-prem).

   

6. llm-finetuning

   5 1 649 4.4 Python

   Discontinued Guide for fine-tuning Llama/Mistral/CodeLlama models and more [GET https://api.github.com/repos/modal-labs/llm-finetuning: 404 - Not Found // See: https://docs.github.com/rest/repos/repos#get-a-repository]

   

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