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sd-pokemon-model-200-steps

Text-to-Image
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stable-diffusion
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  1. README.md +46 -0
  2. checkpoint-100/optimizer.bin +3 -0
  3. checkpoint-100/random_states_0.pkl +3 -0
  4. checkpoint-100/scaler.pt +3 -0
  5. checkpoint-100/scheduler.bin +3 -0
  6. checkpoint-100/unet/config.json +62 -0
  7. checkpoint-100/unet/diffusion_pytorch_model.bin +3 -0
  8. checkpoint-100/unet_ema/config.json +69 -0
  9. checkpoint-100/unet_ema/diffusion_pytorch_model.bin +3 -0
  10. checkpoint-150/optimizer.bin +3 -0
  11. checkpoint-150/random_states_0.pkl +3 -0
  12. checkpoint-150/scaler.pt +3 -0
  13. checkpoint-150/scheduler.bin +3 -0
  14. checkpoint-150/unet/config.json +62 -0
  15. checkpoint-150/unet/diffusion_pytorch_model.bin +3 -0
  16. checkpoint-150/unet_ema/config.json +69 -0
  17. checkpoint-150/unet_ema/diffusion_pytorch_model.bin +3 -0
  18. checkpoint-200/optimizer.bin +3 -0
  19. checkpoint-200/random_states_0.pkl +3 -0
  20. checkpoint-200/scaler.pt +3 -0
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  22. checkpoint-200/unet/config.json +62 -0
  23. checkpoint-200/unet/diffusion_pytorch_model.bin +3 -0
  24. checkpoint-200/unet_ema/config.json +69 -0
  25. checkpoint-200/unet_ema/diffusion_pytorch_model.bin +3 -0
  26. checkpoint-50/optimizer.bin +3 -0
  27. checkpoint-50/random_states_0.pkl +3 -0
  28. checkpoint-50/scaler.pt +3 -0
  29. checkpoint-50/scheduler.bin +3 -0
  30. checkpoint-50/unet/config.json +62 -0
  31. checkpoint-50/unet/diffusion_pytorch_model.bin +3 -0
  32. checkpoint-50/unet_ema/config.json +69 -0
  33. checkpoint-50/unet_ema/diffusion_pytorch_model.bin +3 -0
  34. feature_extractor/preprocessor_config.json +28 -0
  35. logs/text2image-fine-tune/1687316809.960544/events.out.tfevents.1687316809.turing.259181.1 +3 -0
  36. logs/text2image-fine-tune/1687316809.9639866/hparams.yml +50 -0
  37. logs/text2image-fine-tune/events.out.tfevents.1687316809.turing.259181.0 +3 -0
  38. model_index.json +33 -0
  39. safety_checker/config.json +168 -0
  40. safety_checker/pytorch_model.bin +3 -0
  41. scheduler/scheduler_config.json +14 -0
  42. text_encoder/config.json +25 -0
  43. text_encoder/pytorch_model.bin +3 -0
  44. tokenizer/merges.txt +0 -0
  45. tokenizer/special_tokens_map.json +24 -0
  46. tokenizer/tokenizer_config.json +33 -0
  47. tokenizer/vocab.json +0 -0
  48. unet/config.json +62 -0
  49. unet/diffusion_pytorch_model.bin +3 -0
  50. vae/config.json +31 -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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+ datasets:
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+ - lambdalabs/pokemon-blip-captions
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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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+ inference: true
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+ ---
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+
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+ # Text-to-image finetuning - ouvic215/sd-pokemon-model-200-steps
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+
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+ This pipeline was finetuned from **runwayml/stable-diffusion-v1-5** on the **lambdalabs/pokemon-blip-captions** dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['pokemon yoda']:
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+
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+ ![val_imgs_grid](./val_imgs_grid.png)
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+
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+
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+ ## Pipeline usage
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+
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+ You can use the pipeline like so:
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+
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+ ```python
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+ from diffusers import DiffusionPipeline
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+ import torch
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+
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+ pipeline = DiffusionPipeline.from_pretrained("ouvic215/sd-pokemon-model-200-steps", torch_dtype=torch.float16)
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+ prompt = "pokemon yoda"
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+ image = pipeline(prompt).images[0]
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+ image.save("my_image.png")
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+ ```
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+
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+ ## Training info
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+
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+ These are the key hyperparameters used during training:
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+
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+ * Epochs: 100
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+ * Learning rate: 1e-05
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+ * Batch size: 16
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+ * Gradient accumulation steps: 4
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+ * Image resolution: 512
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+ * Mixed-precision: fp16
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