Instructions to use Aloukik21/trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Aloukik21/trainer with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("fill-in-base-model", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Aloukik21/trainer") 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
Download flux-dev/vae/diffusion_pytorch_model.safetensors from Aloukik21/trainer: direct link, hf CLI and curl.
- Browser
- Download file 168 MB
-
https://huggingface.co/Aloukik21/trainer/resolve/main/flux-dev/vae/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://Aloukik21/trainer/flux-dev/vae/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/Aloukik21/trainer/resolve/main/flux-dev/vae/diffusion_pytorch_model.safetensors
168 MB
- Xet hash:
- 5fc08a93307850a89126de1e284972e1a1d7bcbb061ed06edcfc2db5a2669dcd
- Size of remote file:
- 168 MB
- SHA256:
- f5b59a26851551b67ae1fe58d32e76486e1e812def4696a4bea97f16604d40a3
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