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: 581 Bytes
9018dbd | 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 | {
"_class_name": "MiniMaxH3Transformer3DModel",
"_diffusers_version": "0.40.0.dev0",
"_name_or_path": "./tmp/tiny-random/minimax-h3",
"attention_head_dim": 32,
"audio_in_channels": 8,
"ffn_dim": 128,
"final_norm_eps": 1e-05,
"freq_dim": 64,
"hidden_size": 64,
"in_channels": 8,
"norm_eps": 1e-05,
"num_attention_heads": 2,
"num_layers": 2,
"num_refiner_layers": 1,
"patch_size": [
1,
2,
2
],
"qk_norm_eps": 1e-05,
"rope_freq_dim": 4,
"rope_theta": 10000.0,
"text_dim": 32,
"time_embed_dim": 32,
"time_embed_hidden_dim": 64
}
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