Instructions to use AntDish/BACK with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AntDish/BACK 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("AntDish/BACK") 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
| language: | |
| - en | |
| base_model: black-forest-labs/FLUX.1-dev | |
| pipeline_tag: text-to-image | |
| tags: | |
| - flux | |
| - diffusers | |
| - lora | |
| - replicate | |
| ```py | |
| from diffusers import AutoPipelineForText2Image | |
| import torch | |
| pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda') | |
| pipeline.load_lora_weights('AntDish/BACK', weight_name='back.safetensors') | |
| image = pipeline('your prompt').images[0] | |
| ``` | |
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