Text-to-Image
Diffusers
TensorBoard
Safetensors
StableDiffusionPipeline
dreambooth
diffusers-training
stable-diffusion
stable-diffusion-diffusers
Instructions to use DiogoF/Codenames-10000-Text-Encoding-V1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DiogoF/Codenames-10000-Text-Encoding-V1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("DiogoF/Codenames-10000-Text-Encoding-V1", dtype=torch.bfloat16, device_map="cuda") prompt = "the <codenames> style" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- e55963ccc0bf98fb70a60df0dd5494fafa3f33fb1d6e146633b774babee0b75b
- Size of remote file:
- 1.73 GB
- SHA256:
- 6de9096355a0dec734ddedc8dbd25343b9736089acf8c91917147c4ff73473b4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.