Text-to-Image
Diffusers
Trained with AutoTrain
stable-diffusion
stable-diffusion-diffusers
lora
template:sd-lora
Instructions to use Danhearn/spectrogram with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Danhearn/spectrogram with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2-1", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Danhearn/spectrogram") prompt = "mel-spectrograms amen breakbeats" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
| tags: | |
| - autotrain | |
| - stable-diffusion | |
| - stable-diffusion-diffusers | |
| - text-to-image | |
| - diffusers | |
| - lora | |
| - template:sd-lora | |
| base_model: stabilityai/stable-diffusion-2-1 | |
| instance_prompt: mel-spectrograms amen breakbeats | |
| license: openrail++ | |
| # AutoTrain LoRA DreamBooth - Danhearn/spectrogram | |
| These are LoRA adaption weights for stabilityai/stable-diffusion-2-1. The weights were trained on mel-spectrograms amen breakbeats using [DreamBooth](https://dreambooth.github.io/). | |
| LoRA for the text encoder was enabled: True. | |