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--- |
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license: mit |
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tags: |
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- lora |
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- training |
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- runpod |
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- ai-toolkit |
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--- |
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# AI Trainer - RunPod Serverless |
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Single-endpoint multi-model LoRA training with all models cached in this repo. |
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## RunPod Deployment |
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**Set Model field to:** `Aloukik21/trainer` |
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This will cache all models (~240GB) for fast cold starts. |
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## Cached Models |
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| Model Key | Subfolder | Size | |
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|-----------|-----------|------| |
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| flux_dev | flux-dev/ | ~54GB | |
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| flux_schnell | flux-schnell/ | ~54GB | |
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| wan21_14b | wan21-14b/ | ~75GB | |
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| wan22_14b | wan22-14b/ | ~53GB | |
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| qwen_image | qwen-image/ | ~54GB | |
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| accuracy_recovery_adapters | accuracy_recovery_adapters/ | ~3GB | |
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## API Usage |
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### List Models |
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```json |
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{"input": {"action": "list_models"}} |
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``` |
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### Train LoRA |
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```json |
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{ |
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"input": { |
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"action": "train", |
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"model": "flux_dev", |
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"params": { |
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"dataset_path": "/workspace/dataset", |
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"output_path": "/workspace/output", |
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"steps": 1000 |
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} |
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} |
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} |
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``` |
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### Cleanup (between different models) |
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```json |
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{"input": {"action": "cleanup"}} |
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``` |
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## Environment Variables |
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- `HF_TOKEN`: HuggingFace token (required for some gated models) |
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## Auto-Cleanup |
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Handler automatically cleans up GPU memory when switching between different model types. |
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