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https://github.com/elder-plinius/OBLITERATUS.git
synced 2026-04-23 03:36:25 +02:00
Stella Biderman
cbdb772eb9
Adds --gpus flag to obliterate, run, and tourney commands for controlling which GPUs to use (sets CUDA_VISIBLE_DEVICES). Works both locally and with --remote. Models are automatically split across selected GPUs via accelerate's device_map="auto". Also adds gpus field to remote YAML config.
48 lines
1.3 KiB
YAML
48 lines
1.3 KiB
YAML
# Example: Run an ablation study on a remote GPU node via SSH.
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#
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# Usage:
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# obliteratus run examples/remote_gpu_node.yaml
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#
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# The 'remote' section tells Obliteratus to SSH into the specified host,
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# install obliteratus if needed, run the pipeline there, and copy results
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# back to the local machine.
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#
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# You can also use --remote on any command instead of a YAML section:
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# obliteratus obliterate meta-llama/Llama-3.1-8B-Instruct --remote root@gpu-node --ssh-key ~/.ssh/id_rsa
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#
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# Multi-GPU: Models are automatically split across all available GPUs via
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# accelerate's device_map="auto". Use --gpus or the gpus: field to select
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# specific GPUs:
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# obliteratus obliterate model --remote root@gpu-node --gpus 0,1,2,3
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model:
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name: meta-llama/Llama-3.1-8B-Instruct
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task: causal_lm
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dtype: float16
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device: auto
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dataset:
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name: wikitext
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split: test
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max_samples: 500
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strategies:
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- name: layer_removal
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params:
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layer_indices: [10, 11, 12]
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metrics: [perplexity]
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batch_size: 8
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max_length: 512
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output_dir: results/remote_example
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remote:
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host: gpu-node.example.com
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user: root
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port: 22
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ssh_key: ~/.ssh/id_rsa
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remote_dir: /tmp/obliteratus_run
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python: python3
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sync_results: true
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# gpus: "0,1,2,3" # uncomment to select specific GPUs (default: all)
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