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sd-naruto-model

Text-to-Image
Diffusers
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Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
diffusers-training
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[WIP] End of training (multi-commit b536851f57a5ec23d9fe27d0ff0a333c67e9942d859a95e94ee150df063ca6cd)

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  1. README.md +66 -0
  2. checkpoint-1000/optimizer.bin +3 -0
  3. checkpoint-1000/random_states_0.pkl +3 -0
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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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+ 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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+ - diffusers-training
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+ inference: true
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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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+ # Text-to-image finetuning - spockren/sd-naruto-model
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+
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+ This pipeline was finetuned from **runwayml/stable-diffusion-v1-5** on the **lambdalabs/naruto-blip-captions** dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['A <cat-toy> backpack']:
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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("spockren/sd-naruto-model", torch_dtype=torch.float16)
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+ prompt = "A <cat-toy> backpack"
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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: 50
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+ * Learning rate: 1e-05
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+ * Batch size: 1
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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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+
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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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