Instructions to use diffusion-gif/any2ego with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusion-gif/any2ego with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("diffusion-gif/any2ego") 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
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Download LICENSES/UPSTREAM.md from diffusion-gif/any2ego: direct link, hf CLI and curl.
- Browser
- Download file 953 Bytes
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https://huggingface.co/diffusion-gif/any2ego/resolve/main/LICENSES/UPSTREAM.md
- Command line
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hf download hf://diffusion-gif/any2ego/LICENSES/UPSTREAM.md
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curl -L -o UPSTREAM.md https://huggingface.co/diffusion-gif/any2ego/resolve/main/LICENSES/UPSTREAM.md
953 Bytes
Upstream model licenses and attribution
| Upstream model | Declared license | Revision checked |
|---|---|---|
| Wan-AI/Wan2.1-VACE-1.3B | apache-2.0 | 574e6a744642ce3bee319afc31496b88bde8aac4 |
| google/umt5-xxl | apache-2.0 | 66cb9e7e85526fe440a945569e42c72fb6cbc0ad |
| Qwen/Qwen3-VL-8B-Instruct | apache-2.0 | 0c351dd01ed87e9c1b53cbc748cba10e6187ff3b |
| laion/CLIP-ViT-H-14-laion2B-s32B-b79K | mit | 1c2b8495b28150b8a4922ee1c8edee224c284c0c |
Original and derived model components retain their applicable upstream conditions. No dataset redistribution rights are granted by these model licenses. The full Apache 2.0 license text is included. MIT-licensed LAION/OpenCLIP components retain the upstream notice in MIT-OpenCLIP.txt when present.
Public redistribution does not mean these are new training runs, verified robot policies, or reproduced paper metrics. No raw dataset, credentials, account files or training logs are included.