Instructions to use x0mhb788/mohameddddaaaaaad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use x0mhb788/mohameddddaaaaaad with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Gazingstars123/Anima-2.9B", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("x0mhb788/mohameddddaaaaaad") prompt = "<a href=\"https://mohamed.com\">mohamed</a>" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
<a href="https://mohamed.com">mohamed</a>

- Prompt
- <a href="https://mohamed.com">mohamed</a>
- Negative Prompt
- <a href="https://mohamed.com">mohamed</a>
Model description
<a href="https://mohamed.com">mohamed</a>
Trigger words
You should use <a href="https://mohamed.com">mohamed</a> to trigger the image generation.
Download model
Download them in the Files & versions tab.
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Model tree for x0mhb788/mohameddddaaaaaad
Base model
nvidia/Cosmos-Predict2-2B-Text2Image Finetuned
circlestone-labs/Anima Finetuned
Gazingstars123/Anima-2.9B