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textual_inversion_moto

Text-to-Image
Diffusers
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StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
textual_inversion
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  1. README.md +21 -0
  2. checkpoint-1000/optimizer.bin +3 -0
  3. checkpoint-1000/pytorch_model.bin +3 -0
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  12. checkpoint-2000/optimizer.bin +3 -0
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  18. checkpoint-2500/pytorch_model.bin +3 -0
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  27. checkpoint-500/optimizer.bin +3 -0
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  32. feature_extractor/preprocessor_config.json +28 -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.bin +3 -0
  38. learned_embeds-steps-1500.bin +3 -0
  39. learned_embeds-steps-2000.bin +3 -0
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  41. learned_embeds-steps-3000.bin +3 -0
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  45. logs/textual_inversion/1688668078.8436184/hparams.yml +46 -0
  46. logs/textual_inversion/1688668113.9216917/events.out.tfevents.1688668113.asimov.670662.1 +3 -0
  47. logs/textual_inversion/1688668113.923359/hparams.yml +46 -0
  48. logs/textual_inversion/events.out.tfevents.1688668078.asimov.670217.0 +3 -0
  49. logs/textual_inversion/events.out.tfevents.1688668113.asimov.670662.0 +3 -0
  50. model_index.json +33 -0
README.md ADDED
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+
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+ ---
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+ license: creativeml-openrail-m
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+ base_model: runwayml/stable-diffusion-v1-5
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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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+ inference: true
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+ ---
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+
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+ # Textual inversion text2image fine-tuning - manosp/textual_inversion_moto
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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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+ "safety_checker": [
10
+ "stable_diffusion",
11
+ "StableDiffusionSafetyChecker"
12
+ ],
13
+ "scheduler": [
14
+ "diffusers",
15
+ "PNDMScheduler"
16
+ ],
17
+ "text_encoder": [
18
+ "transformers",
19
+ "CLIPTextModel"
20
+ ],
21
+ "tokenizer": [
22
+ "transformers",
23
+ "CLIPTokenizer"
24
+ ],
25
+ "unet": [
26
+ "diffusers",
27
+ "UNet2DConditionModel"
28
+ ],
29
+ "vae": [
30
+ "diffusers",
31
+ "AutoencoderKL"
32
+ ]
33
+ }