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gremlin97
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RemoteDiff

Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
Inference Endpoints
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  1. README.md +48 -0
  2. checkpoint-1000/optimizer.bin +3 -0
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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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+ - None
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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 - gremlin97/RemoteDiff
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+
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+ This pipeline was finetuned from **runwayml/stable-diffusion-v1-5** on the **None** dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['A satellite image of a crop field']:
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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("gremlin97/RemoteDiff", torch_dtype=torch.float16)
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+ prompt = "A satellite image of a crop field"
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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: 2
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+ * Learning rate: 1e-06
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+ * Batch size: 1
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+ * Gradient accumulation steps: 4
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+ * Image resolution: 224
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+ * Mixed-precision: fp16
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+
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+
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+ More information on all the CLI arguments and the environment are available on your [`wandb` run page](https://wandb.ai/gremlin/text2image-fine-tune/runs/tegl1gtv).
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