Instructions to use akshan-main/tiny-diffusion-gemma-modular-pipe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use akshan-main/tiny-diffusion-gemma-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("akshan-main/tiny-diffusion-gemma-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
- Local Apps Settings
- Draw Things
- DiffusionBee
File size: 388 Bytes
922bded | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | {
"confidence_threshold": 0.005,
"eos_token_id": [
1,
106,
50
],
"max_denoising_steps": 48,
"max_new_tokens": 256,
"pad_token_id": 0,
"return_dict_in_generate": true,
"sampler_config": {
"_cls_name": "EntropyBoundSamplerConfig",
"entropy_bound": 0.1
},
"stability_threshold": 1,
"t_max": 0.8,
"t_min": 0.4,
"transformers_version": "5.15.0"
}
|