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  1. README.md +43 -0
  2. checkpoint-1000/model.safetensors +3 -0
  3. checkpoint-1000/optimizer.bin +3 -0
  4. checkpoint-1000/random_states_0.pkl +3 -0
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  32. feature_extractor/preprocessor_config.json +27 -0
  33. image_0.png +0 -0
  34. image_1.png +0 -0
  35. image_2.png +0 -0
  36. image_3.png +0 -0
  37. learned_embeds-steps-1000.safetensors +3 -0
  38. learned_embeds-steps-1500.safetensors +3 -0
  39. learned_embeds-steps-2000.safetensors +3 -0
  40. learned_embeds-steps-2500.safetensors +3 -0
  41. learned_embeds-steps-3000.safetensors +3 -0
  42. learned_embeds-steps-500.safetensors +3 -0
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  44. logs/textual_inversion/1733614113.4177299/events.out.tfevents.1733614113.1241a8f59f4f.6123.1 +3 -0
  45. logs/textual_inversion/1733614113.4266975/hparams.yml +48 -0
  46. logs/textual_inversion/events.out.tfevents.1733614113.1241a8f59f4f.6123.0 +3 -0
  47. model_index.json +38 -0
  48. safety_checker/config.json +29 -0
  49. safety_checker/model.safetensors +3 -0
  50. scheduler/scheduler_config.json +15 -0
README.md ADDED
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+ ---
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+ base_model: runwayml/stable-diffusion-v1-5
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+ library_name: diffusers
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+ license: creativeml-openrail-m
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+ inference: true
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+ tags:
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+ - stable-diffusion
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+ - stable-diffusion-diffusers
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+ - text-to-image
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+ - diffusers
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+ - textual_inversion
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+ - diffusers-training
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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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+ # Textual inversion text2image fine-tuning - iamyblitz/TI_Sinissionist
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+ These are textual inversion adaption weights for runwayml/stable-diffusion-v1-5. You can find some example images in the following.
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+
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+ ![img_0](./image_0.png)
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+ ![img_1](./image_1.png)
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+ ![img_2](./image_2.png)
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+ ![img_3](./image_3.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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