Instructions to use hf-internal-testing/tiny-AudioLDM2Pipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hf-internal-testing/tiny-AudioLDM2Pipeline 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-AudioLDM2Pipeline", 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
| { | |
| "chunk_length_s": 10, | |
| "feature_extractor_type": "ClapFeatureExtractor", | |
| "feature_size": 64, | |
| "fft_window_size": 1024, | |
| "frequency_max": 14000, | |
| "frequency_min": 50, | |
| "hop_length": 7900, | |
| "max_length_s": 10, | |
| "n_fft": 1024, | |
| "nb_frequency_bins": 513, | |
| "nb_max_frames": 1000, | |
| "nb_max_samples": 480000, | |
| "padding": "repeatpad", | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "processor_class": "ClapProcessor", | |
| "return_attention_mask": false, | |
| "sampling_rate": 48000, | |
| "top_db": null, | |
| "truncation": "fusion" | |
| } | |