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  1. README.md +39 -0
  2. checkpoint-1000/model.safetensors +3 -0
  3. checkpoint-1000/optimizer.bin +3 -0
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  28. learned_embeds-steps-1500.safetensors +3 -0
  29. learned_embeds-steps-2000.safetensors +3 -0
  30. learned_embeds-steps-2500.safetensors +3 -0
  31. learned_embeds-steps-3000.safetensors +3 -0
  32. learned_embeds-steps-500.safetensors +3 -0
  33. learned_embeds.safetensors +3 -0
  34. logs/textual_inversion/1711350258.2865915/events.out.tfevents.1711350258.v100-5.240892.1 +3 -0
  35. logs/textual_inversion/1711350258.2913804/hparams.yml +48 -0
  36. logs/textual_inversion/events.out.tfevents.1711350258.v100-5.240892.0 +3 -0
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  40. scheduler/scheduler_config.json +15 -0
  41. text_encoder/config.json +25 -0
  42. text_encoder/model.safetensors +3 -0
  43. tokenizer/added_tokens.json +3 -0
  44. tokenizer/merges.txt +0 -0
  45. tokenizer/special_tokens_map.json +24 -0
  46. tokenizer/tokenizer_config.json +38 -0
  47. tokenizer/vocab.json +0 -0
  48. unet/config.json +68 -0
  49. unet/diffusion_pytorch_model.safetensors +3 -0
  50. vae/config.json +34 -0
README.md ADDED
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+ ---
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+ license: creativeml-openrail-m
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+ library_name: diffusers
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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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+ inference: true
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+ base_model: runwayml/stable-diffusion-v1-5
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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 - justhow/textual_inversion_cat
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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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+
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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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