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models/people_Boris_Becker_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: Boris Becker
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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_Boris_Becker_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: 28.337270736694336
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+ name: ForgetSet clip score of original model mean (~↑)
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+ - type: clip
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+ value: 2.1300061208198953
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+ name: ForgetSet clip score of original model std (~↓)
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+ - type: clip
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+ value: 26.55109739303589
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+ name: ForgetSet clip score of unlearned model mean (↓)
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+ - type: clip
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+ value: 3.7583154297045294
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+ name: ForgetSet clip score of unlearned model std (~↓)
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+ - type: clip
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+ value: 1.7861733436584473
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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: 3.724173412923013
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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: 29.46440076828003
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+ name: RetainSet clip score of original model mean (~↑)
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+ - type: clip
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+ value: 1.2246386976501804
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+ name: RetainSet clip score of original model std (~↓)
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+ - type: clip
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+ value: 31.381918907165527
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+ name: RetainSet clip score of unlearned model mean (↑)
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+ - type: clip
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+ value: 2.038827536797029
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+ name: RetainSet clip score of unlearned model std (~↓)
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+ - type: clip
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+ value: -1.917518138885498
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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: 0.829923298275652
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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: 1.0035234292348227
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+ name: Inference latency seconds mean (↓)
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+ - type: runtime
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+ value: 0.005481156523345093
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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: '[''Boris Becker''] (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: 0.0006084442138671875
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+ name: Runtime init seconds (~↓)
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+ - type: runtime
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+ value: 5.9604644775390625e-06
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+ name: Runtime data loading seconds (~↓)
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+ - type: runtime
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+ value: 1.2567205429077148
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+ name: Runtime training seconds (↓)
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+ - type: runtime
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+ value: 66.52398300170898
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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 Boris Becker 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 Boris Becker.png)
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+ ![img](images/Forget - Photograph of Boris Becker; high definition.png)
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+ ![img](images/Forget - An picture of Boris Becker in the rain.png)
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+ ![img](images/Forget - An picture of Boris Becker 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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