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
- Draw Things
- DiffusionBee
| license: creativeml-openrail-m | |
| tags: | |
| - text-to-image | |
| widget: | |
| - text: mloctst | |
| ### Melov2 Dreambooth model trained by taraxis with [Hugging Face Dreambooth Training Space](https://huggingface.co/spaces/multimodalart/dreambooth-training) with the v1-5 base model | |
| You run your new concept via `diffusers` [Colab Notebook for Inference](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/sd_dreambooth_inference.ipynb). Don't forget to use the concept prompts! | |
| Sample pictures of: | |
| mloctst (use that on your prompt) | |
|  | |