Qlora Alternatives

qlora reviews and mentions

• Fine-Tuning LLMs: A Review of Technologies, Research, Best Practices, Challenges
  1 project | news.ycombinator.com | 22 Oct 2024

  I took a skim through it in the morning - I like the LoRA Learns Less and Forgets Less paper more https://openreview.net/forum?id=aloEru2qCG - it has much more signal in a few pages - also the original QLoRA paper from Dettmers https://arxiv.org/abs/2305.14314 has so many more important morsels.

  But all in all, the review is a reasonable "manual" I guess. I would have liked maybe more instructive comprehensive practical examples, and maybe more mention of other OSS packages for finetuning :))

• FLaNK Stack Weekly for 30 Oct 2023
  24 projects | dev.to | 30 Oct 2023
• I released Marx 3B V3.
  1 project | /r/LocalLLaMA | 25 Oct 2023

  Marx 3B V3 is StableLM 3B 4E1T instruction tuned on EverythingLM Data V3(ShareGPT Format) for 2 epochs using QLoRA.

• Tuning and Testing Llama 2, Flan-T5, and GPT-J with LoRA, Sematic, and Gradio
  2 projects | news.ycombinator.com | 26 Jul 2023

  https://github.com/artidoro/qlora

  The tools and mechanisms to get a model to do what you want is ever so changing, ever so quickly. Build and understand a notebook yourself, and reduce dependencies. You will need to switch them.

• Yet another QLoRA tutorial
  2 projects | /r/LocalLLaMA | 24 Jul 2023

  My own project right now is still in raw generated form, and this now makes me think about trying qlora's scripts since this gives me some confidence I should be able to get it to turn out now that someone else has carved a path and charted the map. I was going to target llamatune which was mentioned here the other day.

• Creating a new Finetuned model
  3 projects | /r/LocalLLaMA | 11 Jul 2023

  Most papers I did read showed at least a thousand, even 10000 at several cases, so I assumed that to be the trend in the case of Low rank adapter(PEFT) training.(source: [2305.14314] QLoRA: Efficient Finetuning of Quantized LLMs (arxiv.org) , Stanford CRFM (Alpaca) and the minimum being openchat/openchat · Hugging Face ; There are a lot more examples)

• [R] LaVIN-lite: Training your own Multimodal Large Language Models on one single GPU with competitive performance! (Technical Details)
  2 projects | /r/MachineLearning | 4 Jul 2023

  4-bit quantization training mainly refers to qlora. Simply put, qlora quantizes the weights of the LLM into 4-bit for storage, while dequantizing them into 16-bit during the training process to ensure training precision. This method significantly reduces GPU memory overhead during training (the training speed should not vary much). This approach is highly suitable to be combined with parameter-efficient methods. However, the original paper was designed for single-modal LLMs and the code has already been wrapped in HuggingFace's library. Therefore, we extracted the core code from HuggingFace's library and migrated it into LaVIN's code. The main principle is to replace all linear layers in LLM with 4-bit quantized layers. Those interested can refer to our implementation in quantization.py and mm_adaptation.py, which is roughly a dozen lines of code.

• [D] To all the machine learning engineers: most difficult model task/type you’ve ever had to work with?
  2 projects | /r/MachineLearning | 3 Jul 2023

  There have been some new development like QLora which help fine-tune LLMs without updating all the weights.

• Finetune MPT-30B using QLORA
  2 projects | /r/LocalLLaMA | 3 Jul 2023

  This might be helpful: https://github.com/artidoro/qlora/issues/10

• is lora fine-tuning on 13B/33B/65B comparable to full fine-tuning?
  1 project | /r/LocalLLaMA | 29 Jun 2023

  curious, since qlora paper only reports lora/qlora comparison for full fine-tuning for small 7B models.for 13B/33B/65B, it does not do so (table 4 in paper)it would be helpful if anyone can please provide links where I can read more on efficacy of lora or disadvantages of lora?

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