Instructions to use aigchacker/Text-Poster with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use aigchacker/Text-Poster 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("aigchacker/Text-Poster") prompt = "Text poster, a couple" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- 2dccac63e58512db882cf548099317aae96b066c0320263ca5fdd35803b47d89
- Size of remote file:
- 134 Bytes
- SHA256:
- 430b576465d17dd26428921a465ebb70e3ec0ab42a23c2df8539e21f5342bd6f
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