Instructions to use fgkhvgkv/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fgkhvgkv/model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fgkhvgkv/model", 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
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Download README.md from fgkhvgkv/model: direct link, hf CLI and curl.
- Browser
- Download file 509 Bytes
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https://huggingface.co/fgkhvgkv/model/resolve/main/README.md
- Command line
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hf download hf://fgkhvgkv/model/README.md
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curl -L -o README.md https://huggingface.co/fgkhvgkv/model/resolve/main/README.md
509 Bytes
metadata
license: mit
pipeline_tag: image-to-3d
LGM Full
This custom pipeline encapsulates the full LGM pipeline, including multi-view diffusion.
It is provided as a resource for the ML for 3D Course.
Original LGM paper: LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation.