https://github.com/truefoundry/llm-finetune
LLM Finetuning with Axolotl with decent defaults + Optional TrueFoundry Experiment Tracking Extension
https://github.com/truefoundry/llm-finetune
llm-finetuning
Last synced: 11 months ago
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LLM Finetuning with Axolotl with decent defaults + Optional TrueFoundry Experiment Tracking Extension
- Host: GitHub
- URL: https://github.com/truefoundry/llm-finetune
- Owner: truefoundry
- Created: 2023-12-07T07:30:29.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2025-06-09T09:19:14.000Z (about 1 year ago)
- Last Synced: 2025-06-09T10:25:33.681Z (about 1 year ago)
- Topics: llm-finetuning
- Language: Python
- Homepage:
- Size: 1.44 MB
- Stars: 6
- Watchers: 2
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
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README
> [!important]
> Please prefer using commits from [release tags](https://github.com/truefoundry/llm-finetune/releases). `main` branch is work in progress and may have partially working commits.
## LLM Finetuning with Truefoundry
Test QLoRA w/ Deepspeed Stage 2
```
./sample_run.sh
```
---
TODO:
- [ ] Setup C/I Tests
- [ ] Track and publish VRAM and Speed benchmarks for popular models and GPUs
---
Generally we always try to optimize for memory footprint because that allows higher batch size and more gpu utilization
Speedup is second priority but we take what we can easily get