Image-Text-to-Video
Diffusers
Safetensors
text-to-video
image-to-video
audio-video-generation
runpod
Instructions to use ovedrive/MiniMax-H3-generator-bf16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ovedrive/MiniMax-H3-generator-bf16 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("ovedrive/MiniMax-H3-generator-bf16", 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
| pipeline_tag: image-text-to-video | |
| library_name: diffusers | |
| license: other | |
| license_name: minimax-h3-community-license-agreement | |
| license_link: LICENSE | |
| base_model: MiniMaxAI/MiniMax-H3 | |
| tags: | |
| - text-to-video | |
| - image-to-video | |
| - audio-video-generation | |
| - runpod | |
| # MiniMax H3 BF16 generator subset | |
| This is a slim, unquantized BF16 generator cache derived from MiniMaxAI/MiniMax-H3 for a split RunPod worker. The model-card text has been modified to describe this subset. | |
| It contains transformer, vae, audio_vae, scheduler, audio_scheduler, and modular_model_index.json. The external H3 conditioner is intentionally not included and is called through its existing Hugging Face Space API. | |
| The weight and configuration files were copied server-side from the official repository without conversion or quantization. Use ovedrive/MiniMax-H3-generator-bf16 in the RunPod endpoint Model field; no Hugging Face model-cache token is required. | |
| See the official model repository for full documentation: https://huggingface.co/MiniMaxAI/MiniMax-H3 | |