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End of training
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---
license: creativeml-openrail-m
base_model: kerianheyi/CS245-fine-tunedSD10200_10600_14122
datasets:
- jytjyt05/t_to_m7
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
inference: true
---
# Text-to-image finetuning - kerianheYi/CS245-fine-tunedSD10600_11000_14122
This pipeline was finetuned from **kerianheyi/CS245-fine-tunedSD10200_10600_14122** on the **jytjyt05/t_to_m7** dataset. Below are some example images generated with the finetuned pipeline using the following prompts: ['A melSpectrogram for piano solo in Major']:
![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("kerianheYi/CS245-fine-tunedSD10600_11000_14122", torch_dtype=torch.float16)
prompt = "A melSpectrogram for piano solo in Major"
image = pipeline(prompt).images[0]
image.save("my_image.png")
```
## Training info
These are the key hyperparameters used during training:
* Epochs: 1
* Learning rate: 1e-05
* Batch size: 1
* Gradient accumulation steps: 4
* Image resolution: 512
* Mixed-precision: fp16