CML_AMP-to-Airgapped
axolotl
| CML_AMP-to-Airgapped | axolotl | |
|---|---|---|
| 1 | 29 | |
| 4 | 6,506 | |
| - | 10.7% | |
| 6.1 | 9.8 | |
| 3 months ago | 2 days ago | |
| Shell | Python | |
| Apache License 2.0 | Apache License 2.0 |
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CML_AMP-to-Airgapped
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?
tracecat - The open source Tines alternative. Automate security workflows at scale with code and no-code.
signal-cli - signal-cli provides an unofficial commandline, JSON-RPC and dbus interface for the Signal messenger.
VoiceCraft - Zero-Shot Speech Editing and Text-to-Speech in the Wild
gpt-llm-trainer
Hybrid-Net - Real-time audio source separation, generate lyrics, chords, beat.
LoRA - Code for loralib, an implementation of "LoRA: Low-Rank Adaptation of Large Language Models"
zenml - ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.
LMFlow - An Extensible Toolkit for Finetuning and Inference of Large Foundation Models. Large Models for All.
FLaNK-python-processors - Many processors
mlc-llm - Universal LLM Deployment Engine with ML Compilation
Fraud-Prevention-With-Cloudera-SSB
koboldcpp - A simple one-file way to run various GGML and GGUF models with KoboldAI's UI