jianzhnie/LLamaTuner
An efficient fine-tuning toolkit for large language models supporting QLoRA, RLHF, DPO on various LLM architectures.
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LLamaTuner provides efficient fine-tuning capabilities for large language models including Llama, Qwen, ChatGLM, and Mixtral. It supports quantization-aware training methods like QLoRA, reinforcement learning techniques such as RLHF and DPO, and integrates with DeepSpeed for ZeRO optimization across multi-node setups. The toolkit enables fine-tuning 7B models on single 8GB GPUs while also supporting distributed training for models exceeding 70B parameters.
Frequently asked
- What is jianzhnie/LLamaTuner?
- An efficient fine-tuning toolkit for large language models supporting QLoRA, RLHF, DPO on various LLM architectures.
- Is LLamaTuner open source?
- Yes — jianzhnie/LLamaTuner is open source, released under the Apache-2.0 license.
- What language is LLamaTuner written in?
- jianzhnie/LLamaTuner is primarily written in Python.
- How popular is LLamaTuner?
- jianzhnie/LLamaTuner has 620 stars on GitHub.
- Where can I find LLamaTuner?
- jianzhnie/LLamaTuner is on GitHub at https://github.com/jianzhnie/LLamaTuner.