## FP32

```python
# !pip install git+https://github.com/huggingface/diffusers.git
from diffusers import DiffusionPipeline
import scipy

model_id = "harmonai/maestro-150k"
pipeline = DiffusionPipeline.from_pretrained(model_id)
pipeline = pipeline.to("cuda")

audios = pipeline(audio_length_in_s=4.0).audios

# To save locally
for audio in audios:
    scipy.io.wavfile.write("maestro_test.wav", pipe.unet.sample_rate, audio.transpose())
    
# To dislay in google colab
import IPython.display as ipd
for audio in audios:
    display(ipd.Audio(audio, rate=pipe.unet.sample_rate))
```

## FP16

Faster at a small loss of quality

```python
# !pip install git+https://github.com/huggingface/diffusers.git
from diffusers import DiffusionPipeline
import scipy
import torch

model_id = "harmonai/maestro-150k"
pipeline = DiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipeline = pipeline.to("cuda")

audios = pipeline(audio_length_in_s=4.0).audios

# To save locally
for audio in audios:
    scipy.io.wavfile.write("maestro_test.wav", pipe.unet.sample_rate, audio.transpose())
    
# To dislay in google colab
import IPython.display as ipd
for audio in audios:
    display(ipd.Audio(audio, rate=pipe.unet.sample_rate))
```