Instructions to use Roman190928/12MLangModel15000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Roman190928/12MLangModel15000 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Roman190928/12MLangModel15000", dtype=torch.bfloat16, device_map="cuda") prompt = "My name is Julien and I like to" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cc353c7e3c7079198634531ec891f70aa7fabff1aac18e6553eab7c8616e1a79
- Size of remote file:
- 72.1 MB
- SHA256:
- dbd3e29ec882db8cfdb00e50b26dd3f3dced77dd785fc504754533a53d882085
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