Instructions to use Brainergy/rraammoonn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Brainergy/rraammoonn with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Brainergy/rraammoonn", 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
Download text_encoder/pytorch_model.bin from Brainergy/rraammoonn: direct link, hf CLI and curl.
- Browser
- Download file 681 MB
-
https://huggingface.co/Brainergy/rraammoonn/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://Brainergy/rraammoonn/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Brainergy/rraammoonn/resolve/main/text_encoder/pytorch_model.bin
681 MB
- Xet hash:
- d710e31af051e02fd0d615196297241d0cd1b6c0b4051b4b19649b26945d53ce
- Size of remote file:
- 681 MB
- SHA256:
- 52730bc9006fa35d3c6120e5e5d29ff6b06686a66c0e521bb31a1b11bc8752a5
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