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pengzju avatar pengzju commented on May 28, 2024

Problem 1: As you can see in README, IKE is not currently supported in the example module. If you want to use IKE to edit the model, you need to to first encode train_set samples and take train_ds as an argument to edit.

like: https://github.com/zjunlp/EasyEdit/blob/main/edit.py#L417

Problem 2: In example module (https://github.com/zjunlp/EasyEdit/tree/main/examples), we provide the script to reprodue experiment. The final edited metric is stored in results.json as follows, and you only need to calculate the corresponding average to get the final edited performance. Later on, we will provide summarize.py to summarize the metrics.

{
    "post": {
        "rewrite_acc": ,
        "rephrase_acc": ,
        "locality": {
            "YOUR_LOCALITY_KEY": ,
            //...
        },
        "portablility": {
            "YOUR_PORTABILITY_KEY": ,
            //...
        },
    },
    "pre": {
        "rewrite_acc": ,
        "rephrase_acc": ,
        "portablility": {
            "YOUR_PORTABILITY_KEY": ,
            //...
        },
    }
}

Problem 3: You can solve the OOM problem in the following three ways

  • git clone code, using a GPU with larger memory (A800, 80GB was used in the original paper)
  • If your resources are limited, consider using device_map='auto' for model parallel(multiple gpus needed), you can refer to the official description of huggingface here
  • Reduce the value of k

from easyedit.

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