Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
dreambooth
diffusers-training
stable-diffusion
stable-diffusion-diffusers
Instructions to use Aedancodes/jj_text_encoder_trained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Aedancodes/jj_text_encoder_trained with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Aedancodes/jj_text_encoder_trained", dtype=torch.bfloat16, device_map="cuda") prompt = "in the style of james jean" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- f83e0358642b5953f5517db8c972e036e84b4989f11c1445d8240500a377a981
- Size of remote file:
- 492 MB
- SHA256:
- b713df6076258e23f13e436ebd3e1b254d45f558a380c67018e2198777583fd9
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