Instructions to use ali-vilab/In-Context-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ali-vilab/In-Context-LoRA with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ali-vilab/In-Context-LoRA") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download portrait-photography.safetensors from ali-vilab/In-Context-LoRA: direct link, hf CLI and curl.
- Browser
- Download file 172 MB
-
https://huggingface.co/ali-vilab/In-Context-LoRA/resolve/main/portrait-photography.safetensors
- Command line
-
hf download hf://ali-vilab/In-Context-LoRA/portrait-photography.safetensors
-
curl -L -o portrait-photography.safetensors https://huggingface.co/ali-vilab/In-Context-LoRA/resolve/main/portrait-photography.safetensors
172 MB
- Xet hash:
- ad7ae5d6292f69dc28111b45f83c12b014a6fe664608d7e5dcb14fb2c0c9471d
- Size of remote file:
- 172 MB
- SHA256:
- d01abbf2f6bef4a33f6f181007816f93ed949851d7d05d8f8bd8fcd5e056c440
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.