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 film-storyboard.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/film-storyboard.safetensors
- Command line
-
hf download hf://ali-vilab/In-Context-LoRA/film-storyboard.safetensors
-
curl -L -o film-storyboard.safetensors https://huggingface.co/ali-vilab/In-Context-LoRA/resolve/main/film-storyboard.safetensors
172 MB
- Xet hash:
- 20d8e075fa2b37f7a2b6e151087c3ec5dc72782d65780699d679c466e0962b03
- Size of remote file:
- 172 MB
- SHA256:
- ec5385ca106e99934ee12a3d17fc99ecf8ed18d52133d80599a9af0377a8ac33
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.