Instructions to use AbstractPhil/geolip-beatrix-sana with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Sana
How to use AbstractPhil/geolip-beatrix-sana with Sana:
# Load the model and infer image from text import torch from app.sana_pipeline import SanaPipeline from torchvision.utils import save_image sana = SanaPipeline("configs/sana_config/1024ms/Sana_1600M_img1024.yaml") sana.from_pretrained("hf://AbstractPhil/geolip-beatrix-sana") image = sana( prompt='a cyberpunk cat with a neon sign that says "Sana"', height=1024, width=1024, guidance_scale=5.0, pag_guidance_scale=2.0, num_inference_steps=18, ) - Diffusers
How to use AbstractPhil/geolip-beatrix-sana with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Efficient-Large-Model/Sana_600M_512px_diffusers", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("AbstractPhil/geolip-beatrix-sana") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Download experiments/e005_lora_neutral_control/eval/sheet_final.jpg from AbstractPhil/geolip-beatrix-sana: direct link, hf CLI and curl.
- Browser
- Download file 468 kB
-
https://huggingface.co/AbstractPhil/geolip-beatrix-sana/resolve/main/experiments/e005_lora_neutral_control/eval/sheet_final.jpg
- Command line
-
hf download hf://AbstractPhil/geolip-beatrix-sana/experiments/e005_lora_neutral_control/eval/sheet_final.jpg
-
curl -L -o sheet_final.jpg https://huggingface.co/AbstractPhil/geolip-beatrix-sana/resolve/main/experiments/e005_lora_neutral_control/eval/sheet_final.jpg
468 kB

- Xet hash:
- 5343753128804dd9003521278c5a1122aad28d89ef24ca386017bf8ab82fa010
- Size of remote file:
- 468 kB
- SHA256:
- 07632ab1c8bd7487bbc1066b78d231edf3fba12bbe7f1a51a35206db5001ac0c
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