Instructions to use tiny-random/minimax-h3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tiny-random/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("tiny-random/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
File size: 896 Bytes
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"_class_name": "AutoencoderKLMiniMaxH3Audio",
"_diffusers_version": "0.40.0.dev0",
"_name_or_path": "./tmp/tiny-random/minimax-h3",
"decoder_dim": 128,
"decoder_kernel_sizes": [
9,
9,
4,
4,
4,
4,
4
],
"decoder_rates": [
5,
5,
2,
2,
2,
2,
2
],
"encoder_dim": 32,
"encoder_rates": [
2,
4,
4,
5,
5
],
"latent_channels": 8,
"latent_dim": 128,
"latents_mean": [
0.0,
0.0,
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0.0,
0.0,
0.0
],
"latents_std": [
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0,
1.0
],
"num_attention_heads": 4,
"resblock_dilation_sizes": [
[
1,
3,
5
],
[
1,
3,
5
],
[
1,
3,
5
]
],
"resblock_kernel_sizes": [
3,
7,
11
],
"sampling_rate": 32000
}
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