Instructions to use XDG-XHS/diff_instruct_1step with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use XDG-XHS/diff_instruct_1step with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("XDG-XHS/diff_instruct_1step", 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
- Local Apps
- Draw Things
- DiffusionBee
File size: 653 Bytes
7b06dae | 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 | {
"_class_name": "LCMScheduler",
"_diffusers_version": "0.29.0",
"beta_end": 0.012,
"beta_schedule": "scaled_linear",
"beta_start": 0.00085,
"clip_sample": false,
"clip_sample_range": 1.0,
"dynamic_thresholding_ratio": 0.995,
"interpolation_type": "linear",
"num_train_timesteps": 1000,
"original_inference_steps": 50,
"prediction_type": "epsilon",
"rescale_betas_zero_snr": false,
"sample_max_value": 1.0,
"set_alpha_to_one": false,
"skip_prk_steps": true,
"steps_offset": 1,
"thresholding": false,
"timestep_scaling": 10.0,
"timestep_spacing": "leading",
"trained_betas": null,
"use_karras_sigmas": false
}
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