Instructions to use zjwfufu/SMD-MiniMax-H3-T2VA-8step with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use zjwfufu/SMD-MiniMax-H3-T2VA-8step with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("MiniMaxAI/MiniMax-H3", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("zjwfufu/SMD-MiniMax-H3-T2VA-8step") prompt = "A man with short gray hair plays a red electric guitar." output = pipe(prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
Download examples/sample.mp4 from zjwfufu/SMD-MiniMax-H3-T2VA-8step: direct link, hf CLI and curl.
- Browser
- Download file 2.86 MB
-
https://huggingface.co/zjwfufu/SMD-MiniMax-H3-T2VA-8step/resolve/main/examples/sample.mp4
- Command line
-
hf download hf://zjwfufu/SMD-MiniMax-H3-T2VA-8step/examples/sample.mp4
-
curl -L -o sample.mp4 https://huggingface.co/zjwfufu/SMD-MiniMax-H3-T2VA-8step/resolve/main/examples/sample.mp4
2.86 MB
- Xet hash:
- 8b126793cc4f2746c9cbaeff3c231183e82d65dec0a13e1d30cf67a16f724dfa
- Size of remote file:
- 2.86 MB
- SHA256:
- e2357dd85a6b17effff23035cd516e6fa98f0308ec2e756b3a2f36a7f3f66137
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