Instructions to use AventIQ-AI/ddpm-cifar10-32_unconditional_image_generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AventIQ-AI/ddpm-cifar10-32_unconditional_image_generation with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("AventIQ-AI/ddpm-cifar10-32_unconditional_image_generation", 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
Download scheduler_config.json from AventIQ-AI/ddpm-cifar10-32_unconditional_image_generation: direct link, hf CLI and curl.
- Browser
- Download file 497 Bytes
-
https://huggingface.co/AventIQ-AI/ddpm-cifar10-32_unconditional_image_generation/resolve/7910f668bba852c76ead0061aa3fe7d9b6027abb/scheduler_config.json
- Command line
-
hf download hf://AventIQ-AI/ddpm-cifar10-32_unconditional_image_generation@7910f668bba852c76ead0061aa3fe7d9b6027abb/scheduler_config.json
-
curl -L -o scheduler_config.json https://huggingface.co/AventIQ-AI/ddpm-cifar10-32_unconditional_image_generation/resolve/7910f668bba852c76ead0061aa3fe7d9b6027abb/scheduler_config.json
497 Bytes
| { | |
| "_class_name": "DDPMScheduler", | |
| "_diffusers_version": "0.32.2", | |
| "beta_end": 0.02, | |
| "beta_schedule": "linear", | |
| "beta_start": 0.0001, | |
| "clip_sample": true, | |
| "clip_sample_range": 1.0, | |
| "dynamic_thresholding_ratio": 0.995, | |
| "num_train_timesteps": 1000, | |
| "prediction_type": "epsilon", | |
| "rescale_betas_zero_snr": false, | |
| "sample_max_value": 1.0, | |
| "steps_offset": 0, | |
| "thresholding": false, | |
| "timestep_spacing": "leading", | |
| "trained_betas": null, | |
| "variance_type": "fixed_small" | |
| } | |