Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
dreambooth
diffusers-training
stable-diffusion
stable-diffusion-diffusers
Instructions to use Aedancodes/hm_text_encoder_trained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Aedancodes/hm_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/hm_text_encoder_trained", dtype=torch.bfloat16, device_map="cuda") prompt = "in the style of hollie mengert" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- fcb2e1e803dee4806df12899ac8ff28db9ec81a3b3cf87500438a446ed6d4975
- Size of remote file:
- 1.97 GB
- SHA256:
- db118422ee4ecb16cf44ab4b830c0a7486dc63100361d0f35d60f96379027578
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