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models/people_Andre_Agassi_uce_000/README.md ADDED
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+ ---
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+ hyperparameters:
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+ pretrained_model_name_or_path: CompVis/stable-diffusion-v1-4
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+ erase_scale: 0.9
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+ preserve_scale: 0.4
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+ lamb: 0.5
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+ save_entire_model: false
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+ edit_concepts: Andre Agassi
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+ guide_concepts: people
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+ preserve_concepts: people
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+ expand_prompts: false
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+ output_dir: assets/models/people_Andre_Agassi_uce_000
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+ device: cuda
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+ compute_runtimes: true
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+ hub_model_id: null
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+ model-index:
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+ - name: None
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+ results:
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+ - task:
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+ type: text-to-image
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+ dataset:
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+ name: Forget set
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+ type: inline-prompts
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+ metrics:
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+ - type: clip
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+ value: 33.872488498687744
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+ name: ForgetSet clip score of original model mean (~↑)
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+ - type: clip
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+ value: 2.0002346898105343
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+ name: ForgetSet clip score of original model std (~↓)
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+ - type: clip
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+ value: 26.573044300079346
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+ name: ForgetSet clip score of unlearned model mean (↓)
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+ - type: clip
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+ value: 2.692283288657135
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+ name: ForgetSet clip score of unlearned model std (~↓)
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+ - type: clip
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+ value: 7.299444198608398
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+ name: ForgetSet clip score difference between original and unlearned mean (↑)
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+ - type: clip
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+ value: 4.513054735033711
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+ name: ForgetSet clip score difference between original and unlearned std (~↓)
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+ - type: clip
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+ value: 30.49503803253174
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+ name: RetainSet clip score of original model mean (~↑)
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+ - type: clip
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+ value: 1.428717359904182
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+ name: RetainSet clip score of original model std (~↓)
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+ - type: clip
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+ value: 31.327601432800293
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+ name: RetainSet clip score of unlearned model mean (↑)
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+ - type: clip
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+ value: 2.066813846186093
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+ name: RetainSet clip score of unlearned model std (~↓)
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+ - type: clip
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+ value: -0.8325634002685547
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+ name: RetainSet clip score difference between original and unlearned mean (↓)
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+ - type: clip
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+ value: 1.585654482594227
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+ name: RetainSet clip score difference between original and unlearned std (~↓)
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+ - type: runtime
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+ value: 3.21586940685908
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+ name: Inference latency seconds mean (↓)
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+ - type: runtime
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+ value: 0.06810925349377793
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+ name: Inference latency seconds std (~↓)
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+ - task:
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+ type: text-to-image
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+ dataset:
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+ name: '[''Andre Agassi''] (forget) and [''people''] (retain) sets'
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+ type: forget-and-retain-together
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+ metrics:
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+ - type: runtime
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+ value: 0.0004436969757080078
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+ name: Runtime init seconds (~↓)
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+ - type: runtime
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+ value: 1.9550323486328125e-05
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+ name: Runtime data loading seconds (~↓)
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+ - type: runtime
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+ value: 3.4498791694641113
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+ name: Runtime training seconds (↓)
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+ - type: runtime
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+ value: 140.17353296279907
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+ name: Runtime eval seconds (~↓)
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the training script had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+
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+ # LoRA text2image fine-tuning - None
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+ These are LoRA adaption weights for CompVis/stable-diffusion-v1-4.
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+ The weights were fine-tuned for forgetting Andre Agassi dataset, while retaining people.
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+ You can find some example images in the following.
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+
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+ ![img](images/Forget - An image of Andre Agassi.png)
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+ ![img](images/Forget - Photograph of Andre Agassi; high definition.png)
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+ ![img](images/Forget - An picture of Andre Agassi in the rain.png)
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+ ![img](images/Forget - An picture of Andre Agassi running.png)
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+ ![img](images/Retain - An image of a child.png)
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+ ![img](images/Retain - Photograph of a child; high definition.png)
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+ ![img](images/Retain - An picture of a child in the rain.png)
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+ ![img](images/Retain - An picture of a child running.png)
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+
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+
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+
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+ ## Intended uses & limitations
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+
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+ #### How to use
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+
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+ ```python
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+ # TODO: add an example code snippet for running this diffusion pipeline
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+ ```
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+
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+ #### Limitations and bias
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+
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+ [TODO: provide examples of latent issues and potential remediations]
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+
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+ ## Training details
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+
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+ [TODO: describe the data used to train the model]
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