Instructions to use moulichand/Personalised with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use moulichand/Personalised with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("moulichand/Personalised", dtype=torch.bfloat16, device_map="cuda") prompt = "Photo of Moulichandbm, a young man with black hair, wearing an orange T-shirt" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Commit History
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Upload README.md
c77a9cb -
Upload prompt.txt
5cd2937 -
Upload training_params.json
65e7b0f -
Upload pytorch_lora_weights.safetensors
13b328b -
initial commit
Birudugadda Mouli Chandc7f1372