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CLI: add --launcher option, support launcher args, cleanup, refactor (#2924)

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* add --launcher option; explicit True/False bool args; small cleanup

* refactor

* add torchrun, accelerate cli args

* add rdzv arg default + tests

* update _quarto

* coderabbit

* fix

* we can't set rdvz_id independently across nodes

* coderabbit

* fix tests
This commit is contained in:
Dan Saunders
2025-07-30 15:46:56 -04:00
committed by GitHub
parent 22810c97b7
commit bb1cae1a20
31 changed files with 1417 additions and 541 deletions
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26
docs/cli.qmd
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@@ -23,6 +23,20 @@ axolotl <command> [config.yml] [options]
The config file can be local or a URL to a raw YAML file.
### Launcher Arguments
For commands that support multi-GPU (`train`, `evaluate`, ...), you can pass launcher-specific arguments using the `--` separator:
```bash
# Pass torchrun arguments
axolotl train config.yml --launcher torchrun -- --nproc_per_node=2 --nnodes=1
# Pass accelerate arguments
axolotl train config.yml --launcher accelerate -- --config_file=accelerate_config.yml --num_processes=4
```
Arguments after `--` are passed directly to the launcher (torchrun, accelerate launch, etc.).
## Command Reference
### fetch
@@ -80,7 +94,11 @@ axolotl train config.yml \
--num-epochs 3
# Training without accelerate
axolotl train config.yml --no-accelerate
axolotl train config.yml --launcher python
# Pass launcher-specific arguments using -- separator
axolotl train config.yml --launcher torchrun -- --nproc_per_node=2 --nnodes=1
axolotl train config.yml --launcher accelerate -- --config_file=accelerate_config.yml
# Resume training from checkpoint
axolotl train config.yml --resume-from-checkpoint path/to/checkpoint
@@ -175,6 +193,9 @@ Evaluates a model's performance (loss etc) on the train and eval datasets.
```bash
# Basic evaluation
axolotl evaluate config.yml
# Evaluation with launcher arguments
axolotl evaluate config.yml --launcher torchrun -- --nproc_per_node=2
```
### lm-eval
@@ -287,9 +308,6 @@ axolotl preprocess config.yml --cloud cloud_config.yml
# Train on cloud
axolotl train config.yml --cloud cloud_config.yml
# Train without accelerate on cloud
axolotl train config.yml --cloud cloud_config.yml --no-accelerate
# Run lm-eval on cloud
axolotl lm-eval config.yml --cloud cloud_config.yml
```