Image-to-3D
Diffusers
Safetensors
LGMFullPipeline
text-to-3d
3d-generation
3d-gaussian-splatting
gaussian-splatting
multi-view-diffusion
lgm
objaverse
research
computer-graphics
Instructions to use WasabiOctopus/LGM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WasabiOctopus/LGM with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("WasabiOctopus/LGM", 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
File size: 511 Bytes
52e2add | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 | {
"_class_name": "LGMFullPipeline",
"_diffusers_version": "0.25.0",
"feature_extractor": ["transformers", "CLIPImageProcessor"],
"image_encoder": ["transformers", "CLIPVisionModel"],
"requires_safety_checker": false,
"scheduler": ["diffusers", "DDIMScheduler"],
"text_encoder": ["transformers", "CLIPTextModel"],
"tokenizer": ["transformers", "CLIPTokenizer"],
"unet": ["mv_unet", "MultiViewUNetModel"],
"vae": ["diffusers", "AutoencoderKL"],
"lgm": ["lgm", "LGM"]
}
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