axolotl
| qlora-fine-tune | axolotl | |
|---|---|---|
| 6 | 29 | |
| 164 | 6,506 | |
| - | 10.7% | |
| 3.8 | 9.8 | |
| about 1 year ago | 1 day ago | |
| Python | Python | |
| - | Apache License 2.0 |
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qlora-fine-tune
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Help with QLoRA Fine Tune
I'm following nearly the same example from the this repository: https://github.com/mzbac/qlora-fine-tune
- What have you done with finetuning and LoRAs?
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Can I just create a dataset and train a model with QLoRA?
I have successfully used this repo. Works amazingly well. https://github.com/mzbac/qlora-fine-tune
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I would like to try my hand at finetuning some models. What is the best way to start? I have some questions that I'd appreciate your help on.
For all in one out of box scripts, have a look at https://github.com/mzbac/qlora-fine-tune
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Fine-tune the WizardLM 13B using chat history from ChatGPT with QLoRa
In case you guys are interested in fine-tuning similar models, I have put all my scripts here https://github.com/mzbac/qlora-fine-tune
axolotl
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Ask HN: Most efficient way to fine-tune an LLM in 2024?
The approach I see used is axolotl with QLoRA using cloud GPUs which can be quite cheap.
https://github.com/OpenAccess-AI-Collective/axolotl
- FLaNK AI - 01 April 2024
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LoRA from Scratch implementation for LLM finetuning
https://github.com/OpenAccess-AI-Collective/axolotl
- Optimized Triton Kernels for full fine tunes
- Axolotl
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Let’s Collaborate to Build a High-Quality, Open-Source Dataset for LLMs!
One option is to look at what Axolotl uses. They have a list of different dataset formats that they support. They're mostly in JSON with specific field names, so you could start putting a dataset together with a text editor or a JSON editor.
- Axolotl: Streamline fine-tuning of AI models
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Dataset Creation Tools?
You can save that overall set into a json file and load it up as training data in whatever you're using. I'm using axolotl for it at the moment. Though a GUI based option is probably best for the first couple of tries until you get a feel for the options.
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Progress on Reproducing Phi-1/1.5
Looking forward to the results! If it turns out the dataset is reproducible, then it might be a good candidate for ReLora training on axolotl!
What are some alternatives?
xTuring - Build, customize and control you own LLMs. From data pre-processing to fine-tuning, xTuring provides an easy way to personalize open-source LLMs. Join our discord community: https://discord.gg/TgHXuSJEk6
signal-cli - signal-cli provides an unofficial commandline, JSON-RPC and dbus interface for the Signal messenger.
gpt-llm-trainer
LoRA - Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"
LMFlow - An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. Large Models for All.
mlc-llm - Universal LLM Deployment Engine with ML Compilation
koboldcpp - A simple one-file way to run various GGML and GGUF models with KoboldAI's UI
OpenPipe - Turn expensive prompts into cheap fine-tuned models
tracecat - The open source Tines alternative. Automate security workflows at scale with code and no-code.
libsignal - Home to the Signal Protocol as well as other cryptographic primitives which make Signal possible.
org.signal.Signal