Instructions to use codermert/tugce2-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use codermert/tugce2-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("codermert/tugce2-lora") prompt = "DHANUSH" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 2c00c8268fd5f406290dd11bc7ae5943d3930250ca036d4effe1c012a29dc8e9
- Size of remote file:
- 173 MB
- SHA256:
- bafaa0e4ffbbf318b459d4b6b2a18d5fdfc860a1426a824abfe4279aa19d1a0a
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