Instructions to use hf-internal-testing/tiny-AceStepPipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hf-internal-testing/tiny-AceStepPipeline 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-AceStepPipeline", 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: 466 Bytes
29f2820 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | {
"_class_name": "AceStepAudioTokenDetokenizer",
"_diffusers_version": "0.39.0.dev0",
"attention_bias": false,
"attention_dropout": 0.0,
"audio_acoustic_hidden_dim": 8,
"head_dim": 8,
"hidden_size": 32,
"intermediate_size": 64,
"layer_types": null,
"num_attention_heads": 4,
"num_attention_pooler_hidden_layers": 1,
"num_key_value_heads": 2,
"pool_window_size": 2,
"rms_norm_eps": 1e-06,
"rope_theta": 10000.0,
"sliding_window": 16
}
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