Instructions to use bytefid/ChattyBytex with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bytefid/ChattyBytex 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("bytefid/ChattyBytex") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 8e77e0ea929d047e6abebd692f23982a18c279e1d96af7256a789199e1aaf62b
- Size of remote file:
- 1.47 kB
- SHA256:
- 4f99f9119d2bf82f22cd8c75d3032e7113e09bef4f8f51c36b0cc9746daae1fd
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