Instructions to use taraxis/melov2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use taraxis/melov2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("taraxis/melov2", dtype=torch.bfloat16, device_map="cuda") prompt = "mloctst" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 5e360b834db77741735d68927adddf7302d10c4bf9887062a4e7271fb571a1ce
- Size of remote file:
- 3.44 GB
- SHA256:
- 1ec13df3eca8860bea95807ffbdae27edf321073c7092bda55a70bd9ecbecf02
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.