Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
diffusers-training
Instructions to use MohamedAcadys/PointConImageModelV2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MohamedAcadys/PointConImageModelV2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MohamedAcadys/PointConImageModelV2", torch_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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 5b0b61b2ca353da825243c4137138835a20b843754cbdc1da49cb5ef9185b99b
- Size of remote file:
- 6.88 GB
- SHA256:
- c1f25b0eabc10b46ff56145eb4515d3cdd9ae7ee2e1b9aa89117da074f04fa0a
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