AI Trainer - RunPod Serverless

Single-endpoint multi-model LoRA training with all models cached in this repo.

RunPod Deployment

Set Model field to: Aloukik21/trainer

This will cache all models (~240GB) for fast cold starts.

Cached Models

Model Key	Subfolder	Size
flux_dev	flux-dev/	~54GB
flux_schnell	flux-schnell/	~54GB
wan21_14b	wan21-14b/	~75GB
wan22_14b	wan22-14b/	~53GB
qwen_image	qwen-image/	~54GB
accuracy_recovery_adapters	accuracy_recovery_adapters/	~3GB

API Usage

List Models

{"input": {"action": "list_models"}}

Train LoRA

{
  "input": {
    "action": "train",
    "model": "flux_dev",
    "params": {
      "dataset_path": "/workspace/dataset",
      "output_path": "/workspace/output",
      "steps": 1000
    }
  }
}

Cleanup (between different models)

{"input": {"action": "cleanup"}}

Environment Variables

• HF_TOKEN: HuggingFace token (required for some gated models)

Auto-Cleanup

Handler automatically cleans up GPU memory when switching between different model types.