Instructions to use InstantX/flux-dev-de-distill-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use InstantX/flux-dev-de-distill-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("InstantX/flux-dev-de-distill-diffusers", 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
| license: other | |
| license_name: flux-1-dev-non-commercial-license | |
| license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md | |
| language: | |
| - en | |
| base_model: | |
| - black-forest-labs/FLUX.1-dev | |
| library_name: diffusers | |
| ## Model Details | |
| This is a diffusers version of [nyanko7/flux-dev-de-distill](https://huggingface.co/nyanko7/flux-dev-de-distill) that generates exactly the same results as the original. But please note that there is a certain degree of quality degradation in comparison with [black-forest-labs/FLUX.1-dev](https://huggingface.co/black-forest-labs/FLUX.1-dev) in our test. | |
| We are training its fine-tuning models to check its effectiveness, feel free to let us know if you have any interesting findings. | |
| ## Usage | |
| ```python | |
| import torch | |
| from diffusers import FluxTransformer2DModel | |
| from pipeline_flux_de_distill import FluxPipeline | |
| model_path = "black-forest-labs/FLUX.1-dev" | |
| transformer = FluxTransformer2DModel.from_pretrained( | |
| "InstantX/flux-dev-de-distill-diffusers", | |
| torch_dtype=torch.bfloat16 | |
| ) | |
| pipeline = FluxPipeline.from_pretrained(model_path, transformer=transformer, torch_dtype=torch.bfloat16).to("cuda") | |
| prompt = "a tiny astronaut hatching from an egg on the moon" | |
| negative_prompt = "bad photo" | |
| image = pipeline( | |
| prompt=prompt, | |
| negative_prompt=negative_prompt, | |
| guidance_scale=3.5, | |
| num_inference_steps=24, | |
| ).images[0] | |
| image.save("de-distill.jpg") | |
| ``` | |
| ## Other Resources | |
| - [MinusZoneAI/flux-dev-de-distill-fp8](https://huggingface.co/MinusZoneAI/flux-dev-de-distill-fp8), [TheYuriLover/flux-dev-de-distill-GGUF](https://huggingface.co/TheYuriLover/flux-dev-de-distill-GGUF) | |
| - [ashen0209/Flux-Dev2Pro](https://huggingface.co/ashen0209/Flux-Dev2Pro), [ostris/OpenFLUX.1](https://huggingface.co/ostris/OpenFLUX.1) | |
| ## Acknowledgements | |
| This project is co-sponsored by [HuggingFace](https://huggingface.co/) and [fal](https://huggingface.co/fal). |