Text-to-Image
Diffusers
Safetensors
FluxPipeline
FLUX
FLUX-diffusers
diffusers-training
textual_inversion
Instructions to use rangwani-harsh/logs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rangwani-harsh/logs 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_textual_inversion("rangwani-harsh/logs") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 3e12ee65bb88483cab5019b18ef9a84fe5e968e37e79e1bab4c5ebf3ad2c875c
- Size of remote file:
- 1.25 MB
- SHA256:
- 53f8eddb37a38e23420ca6cae9158cfe781785cd5e42b93c7e79c9d42c8ae27a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.