Instructions to use Insta360-Research/DiT360-Panorama-Image-Generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Insta360-Research/DiT360-Panorama-Image-Generation with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Insta360-Research/DiT360-Panorama-Image-Generation", 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
Update inference.py
Browse files- inference.py +1 -1
inference.py
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@@ -3,7 +3,7 @@ import torch
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device = torch.device("cuda:0")
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pipe = DiT360Pipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.float16).to(device)
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pipe.load_lora_weights("
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image = pipe(
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"This is a panorama. The image shows a medieval castle stands proudly on a hilltop surrounded by autumn forests, with golden light spilling across the landscape.",
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device = torch.device("cuda:0")
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pipe = DiT360Pipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.float16).to(device)
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pipe.load_lora_weights("Insta360-Research/DiT360-Panorama-Image-Generation")
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image = pipe(
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"This is a panorama. The image shows a medieval castle stands proudly on a hilltop surrounded by autumn forests, with golden light spilling across the landscape.",
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