Instructions to use TensorStack/TextEncoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TensorStack/TextEncoder with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("TensorStack/TextEncoder", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e68292f56d7c4b4828f7f50a8daf45bac053c442a1d41548809e8767c89d7444
- Size of remote file:
- 11.4 GB
- SHA256:
- 7b8850f1961e1cf8a77cca4c964a358d303f490833c6c087d0cff4b2f99db2af
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