Instructions to use camenduru/tpu-train-tutorial-pt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use camenduru/tpu-train-tutorial-pt with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("camenduru/tpu-train-tutorial-pt", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
Download unet/diffusion_pytorch_model.bin from camenduru/tpu-train-tutorial-pt: direct link, hf CLI and curl.
- Browser
- Download file 3.44 GB
-
https://huggingface.co/camenduru/tpu-train-tutorial-pt/resolve/main/unet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://camenduru/tpu-train-tutorial-pt/unet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/camenduru/tpu-train-tutorial-pt/resolve/main/unet/diffusion_pytorch_model.bin
3.44 GB
- Xet hash:
- fb4879d0ec378ba882924c7c21b168150eff7767bd9a16694f0757e9b3b22b34
- Size of remote file:
- 3.44 GB
- SHA256:
- 4924a3f51a49b0c11a9fb1fa6f62ae88e5f15f9a2b9cf8926289038bbd30aa9f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.