Instructions to use mathieuripert/tolmer-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mathieuripert/tolmer-model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2-1", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("mathieuripert/tolmer-model") prompt = "A painting from Michel Tolmer" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 3e4b879eab7c4665a2d10a2f165b933b5d2154aa483202586dca62f508b12f4e
- Size of remote file:
- 6.85 MB
- SHA256:
- e82c212bf8fc83e346f4a1b37bd5ca58f4407d151247254e4cd9a9da19978d04
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