Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusion3Pipeline
diffusers-training
template:sd-lora
sd3
sd3-diffusers
Instructions to use tomy600098/TunedModel_Spodoptera-lf_2_sd3.5_remove with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tomy600098/TunedModel_Spodoptera-lf_2_sd3.5_remove with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("tomy600098/TunedModel_Spodoptera-lf_2_sd3.5_remove", dtype=torch.bfloat16, device_map="cuda") prompt = "Eggs of Spodoptera were observed on the surface of a passion fruit leaf" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- cec40a717abbf1ca90fe171c4c1efaf06cad576aeee6e6d8088a00d17b72c193
- Size of remote file:
- 4.99 GB
- SHA256:
- 8e0e98242fed1de128a73ee6fee174aa30186c66f7d70811c8ebf67d72067f38
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.