End of training

README.md

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+
+---
+license: creativeml-openrail-m
+base_model: CompVis/stable-diffusion-v1-4
+datasets:
+- None
+tags:
+- stable-diffusion
+- stable-diffusion-diffusers
+- text-to-image
+- diffusers
+inference: true
+---
+    
+# Text-to-image finetuning - Aminrabi/diff1000
+
+This pipeline was finetuned from **CompVis/stable-diffusion-v1-4** on the **None** dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['[necklace in flowers shape]']: 
+
+![val_imgs_grid](./val_imgs_grid.png)
+
+
+## Pipeline usage
+
+You can use the pipeline like so:
+
+```python
+from diffusers import DiffusionPipeline
+import torch
+
+pipeline = DiffusionPipeline.from_pretrained("Aminrabi/diff1000", torch_dtype=torch.float16)
+prompt = "[necklace in flowers shape]"
+image = pipeline(prompt).images[0]
+image.save("my_image.png")
+```
+
+## Training info
+
+These are the key hyperparameters used during training:
+
+* Epochs: 77
+* Learning rate: 1e-05
+* Batch size: 1
+* Gradient accumulation steps: 4
+* Image resolution: 512
+* Mixed-precision: fp16
+

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