Instructions to use naclbit/trinart_stable_diffusion_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use naclbit/trinart_stable_diffusion_v2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("naclbit/trinart_stable_diffusion_v2", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
Update license
Hi @naclbit ! Cool model! I realized the model is a derivative of Stable Diffusion (SD). According to the SD "CreativeML OpenRAIL-M" license, derivatives of SD must include -at minimum- the same use restrictions as the ones in the SD license. Your model is under an Apache 2.0 license and therefore is not in compliance with the SD license, as it should include the restrictions as part of the license.
With Open & Responsible AI licenses model developers are making efforts towards an open and responsible use of ML Models, users of these models should respect that. AI's open and responsible sharing culture depends on all of us, the AI community.
In my opinion, it would be very nice from you if you could update the license for your model in order to respect the SD license, as by using the SD model you agreed to the license. You can already use OpenRAIL licenses' tags in the hub, by the way, such us the BigScience OpenRAIL-M or CreativeML OpenRAIL-M.
Take care!🤗