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models/scenes_orchard_uce_000/README.md

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+---
+hyperparameters:
+  pretrained_model_name_or_path: CompVis/stable-diffusion-v1-4
+  erase_scale: 30.0
+  preserve_scale: 0.01
+  lamb: 0.01
+  save_entire_model: false
+  edit_concepts: an orchard scene
+  guide_concepts: scenes
+  preserve_concepts: scenes
+  expand_prompts: false
+  output_dir: assets/models/scenes_orchard_uce_000
+  device: cuda
+  compute_runtimes: true
+  hub_model_id: null
+model-index:
+- name: None
+  results:
+  - task:
+      type: text-to-image
+    dataset:
+      name: Forget set
+      type: inline-prompts
+    metrics:
+    - type: clip
+      value: 35.884714126586914
+      name: ForgetSet clip score of original model mean (~↑)
+    - type: clip
+      value: 2.60235833807125
+      name: ForgetSet clip score of original model std (~↓)
+    - type: clip
+      value: 32.25832509994507
+      name: ForgetSet clip score of unlearned model mean (↓)
+    - type: clip
+      value: 2.102430119056124
+      name: ForgetSet clip score of unlearned model std (~↓)
+    - type: clip
+      value: 3.6263890266418457
+      name: ForgetSet clip score difference between original and unlearned mean (↑)
+    - type: clip
+      value: 4.377352625802537
+      name: ForgetSet clip score difference between original and unlearned std (~↓)
+    - type: clip
+      value: 29.47777557373047
+      name: RetainSet clip score of original model mean (~↑)
+    - type: clip
+      value: 1.0017547940821476
+      name: RetainSet clip score of original model std (~↓)
+    - type: clip
+      value: 29.79594087600708
+      name: RetainSet clip score of unlearned model mean (↑)
+    - type: clip
+      value: 2.3473106155883325
+      name: RetainSet clip score of unlearned model std (~↓)
+    - type: clip
+      value: -0.31816530227661133
+      name: RetainSet clip score difference between original and unlearned mean (↓)
+    - type: clip
+      value: 1.6578004439023164
+      name: RetainSet clip score difference between original and unlearned std (~↓)
+    - type: runtime
+      value: 4.258222341537476
+      name: Inference latency seconds mean (↓)
+    - type: runtime
+      value: 0.11003008822400075
+      name: Inference latency seconds std (~↓)
+  - task:
+      type: text-to-image
+    dataset:
+      name: '[''an orchard scene''] (forget) and [''scenes''] (retain) sets'
+      type: forget-and-retain-together
+    metrics:
+    - type: runtime
+      value: 0.003545045852661133
+      name: Runtime init seconds (~↓)
+    - type: runtime
+      value: 1.0967254638671875e-05
+      name: Runtime data loading seconds (~↓)
+    - type: runtime
+      value: 3.1458981037139893
+      name: Runtime training seconds (↓)
+    - type: runtime
+      value: 105.44764542579651
+      name: Runtime eval seconds (~↓)
+---
+
+<!-- This model card has been generated automatically according to the information the training script had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+
+# LoRA text2image fine-tuning - None
+These are LoRA adaption weights for CompVis/stable-diffusion-v1-4.
+The weights were fine-tuned for forgetting an orchard scene dataset, while retaining scenes.
+You can find some example images in the following.
+
+![img](images/Forget - An image of an orchard scene.png)
+![img](images/Forget - Photograph of an orchard scene; high definition.png)
+![img](images/Forget - An picture of an orchard scene full of people.png)
+![img](images/Forget - An picture of an orchard scene during the night.png)
+![img](images/Retain - An image of the moon.png)
+![img](images/Retain - Photograph of the moon; high definition.png)
+![img](images/Retain - An picture of the moon full of people.png)
+![img](images/Retain - An picture of the moon during the night.png)
+
+
+
+## Intended uses & limitations
+
+#### How to use
+
+```python
+# TODO: add an example code snippet for running this diffusion pipeline
+```
+
+#### Limitations and bias
+
+[TODO: provide examples of latent issues and potential remediations]
+
+## Training details
+
+[TODO: describe the data used to train the model]

models/scenes_orchard_uce_000/uce_sd_weights.safetensors

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