Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
dreambooth
diffusers-training
stable-diffusion
stable-diffusion-diffusers
Instructions to use Aedancodes/jj_text_encoder_trainedv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Aedancodes/jj_text_encoder_trainedv2 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_trainedv2", dtype=torch.bfloat16, device_map="cuda") prompt = "An image in the style of zhr james jean" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- e209ea7d35f6391824c7826ae3c327ce234a08630131b2a616f4bd8ab95e0e61
- Size of remote file:
- 492 MB
- SHA256:
- d231e11a22ddbea0785c77cc1d9cc223c39257b5a0ecf481a67b6318543e53fc
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