Instructions to use diffusers-internal-dev/tiny-minimax-h3-modular-pipe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers-internal-dev/tiny-minimax-h3-modular-pipe with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("diffusers-internal-dev/tiny-minimax-h3-modular-pipe", 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
File size: 713 Bytes
43463e6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 | {
"_class_name": "MiniMaxH3Pipeline",
"_diffusers_version": "0.40.0.dev0",
"text_encoder": [
"transformers",
"Qwen3VLForConditionalGeneration"
],
"tokenizer": [
"transformers",
"Qwen2Tokenizer"
],
"processor": [
"transformers",
"Qwen3VLProcessor"
],
"vae": [
"diffusers",
"AutoencoderKLMiniMaxH3"
],
"audio_vae": [
"diffusers",
"AutoencoderKLMiniMaxH3Audio"
],
"transformer": [
"diffusers",
"MiniMaxH3Transformer3DModel"
],
"transformer_ref": [
"diffusers",
"MiniMaxH3Transformer3DModel"
],
"scheduler": [
"diffusers",
"MiniMaxH3Scheduler"
],
"audio_scheduler": [
"diffusers",
"MiniMaxH3Scheduler"
]
} |