Instructions to use hf-internal-testing/tiny-minimax-h3-modular-pipe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hf-internal-testing/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("hf-internal-testing/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: 819 Bytes
f050e61 | 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 41 42 43 44 45 46 | {
"_class_name": "AutoencoderKLMiniMaxH3",
"_diffusers_version": "0.40.0.dev0",
"block_out_channels": [
8,
16
],
"clip_length": 17,
"decoder_attention_head_dim": 8,
"decoder_ffn_mult": 2,
"decoder_norm_eps": 1e-05,
"decoder_num_attention_heads": 2,
"decoder_num_layers": 2,
"decoder_num_register_tokens": 2,
"decoder_rope_dim_ratio": 0.75,
"decoder_rope_theta": 100.0,
"in_channels": 3,
"latent_channels": 4,
"latents_mean": [
0.0,
0.0,
0.0,
0.0
],
"latents_std": [
1.0,
1.0,
1.0,
1.0
],
"layers_per_block": 1,
"norm_eps": 1e-06,
"norm_num_groups": 8,
"out_channels": 3,
"spatial_downsample_factors": [
4,
4
],
"spatial_padding_mode": "reflect",
"temporal_downsample_factors": [
2,
2
],
"token_drop": 3
}
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