Instructions to use Efficient-Large-Model/Open-H3-Regenerate-2K with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Efficient-Large-Model/Open-H3-Regenerate-2K with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MiniMaxAI/MiniMax-H3", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Efficient-Large-Model/Open-H3-Regenerate-2K") 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
Download base_model/tokenizer/tokenizer.json from Efficient-Large-Model/Open-H3-Regenerate-2K: direct link, hf CLI and curl.
- Browser
- Download file 7.03 MB
-
https://huggingface.co/Efficient-Large-Model/Open-H3-Regenerate-2K/resolve/main/base_model/tokenizer/tokenizer.json
- Command line
-
hf download hf://Efficient-Large-Model/Open-H3-Regenerate-2K/base_model/tokenizer/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/Efficient-Large-Model/Open-H3-Regenerate-2K/resolve/main/base_model/tokenizer/tokenizer.json
7.03 MB
File too large to display, you can check the raw version instead.