Image-Text-to-Video
Diffusers
Safetensors
MiniMaxH3ModularPipeline
text-to-video
image-to-video
video-to-video
text-to-audio-video
image-to-audio-video
image-text-to-audio-video
video-to-audio-video
audio-to-audio-video
audio-video-generation
multimodal
synchronized-audio-video
reference-to-audio-video
Instructions to use MiniMaxAI/MiniMax-H3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MiniMaxAI/MiniMax-H3 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") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
| set -euo pipefail | |
| # Create the prompt-expansion task and capture its runtime ID. | |
| task_id=$( | |
| curl --silent --show-error \ | |
| --request POST \ | |
| --url "$MINIMAX_API_BASE/v2/h3_context_ir" \ | |
| --header "Authorization: Bearer $TOKEN" \ | |
| --header 'Content-Type: application/json' \ | |
| --data '{ | |
| "model": "MiniMax-H3", | |
| "content": [ | |
| { | |
| "type": "text", | |
| "text": "Epic space-opera theatrical teaser: a female captain stands alone before a massive observation window as the last fleet gathers and jumps away in a blinding flash, the bridge shaking, leaving her behind." | |
| } | |
| ], | |
| "duration": 10, | |
| "ratio": "16:9" | |
| }' | | |
| jq -er '.task_id' | |
| ) | |
| # Query again while the task is queued or running. | |
| context_ir_result=$( | |
| curl --silent --show-error \ | |
| --request GET \ | |
| --url "$MINIMAX_API_BASE/v2/query/video_generation/$task_id" \ | |
| --header "Authorization: Bearer $TOKEN" | |
| ) | |
| echo "$context_ir_result" | jq . | |
| # Export the complete expanded prompt for H3-Base and regeneration. | |
| EXPANDED_PROMPT=$(echo "$context_ir_result" | jq -er '.task.content.prompt') | |