Instructions to use tiny-random/flux2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tiny-random/flux2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("tiny-random/flux2", 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 vae/diffusion_pytorch_model.safetensors from tiny-random/flux2: direct link, hf CLI and curl.
- Browser
- Download file 458 kB
-
https://huggingface.co/tiny-random/flux2/resolve/main/vae/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://tiny-random/flux2/vae/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/tiny-random/flux2/resolve/main/vae/diffusion_pytorch_model.safetensors
458 kB
- Xet hash:
- e3b99440b07673266d48b98b4aec9f05f65e0c32f40324c559ff8fc6b5442419
- Size of remote file:
- 458 kB
- SHA256:
- 26425f0c556b86d314db50c2638d6d3f401002c847dcca1fc22984c1c7b764e6
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