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
Download model/generation_config.json from akshan-main/tiny-diffusion-gemma-modular-pipe: direct link, hf CLI and curl.
- Browser
- Download file 388 Bytes
-
https://huggingface.co/akshan-main/tiny-diffusion-gemma-modular-pipe/resolve/main/model/generation_config.json
- Command line
-
hf download hf://akshan-main/tiny-diffusion-gemma-modular-pipe/model/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/akshan-main/tiny-diffusion-gemma-modular-pipe/resolve/main/model/generation_config.json
388 Bytes
| { | |
| "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" | |
| } | |