Text-to-Image
Diffusers
Safetensors
StableDiffusionPipeline
stable-diffusion
stable-diffusion-diffusers
Noosphere
Dreamlike
Rainbowpatch
Instructions to use Yntec/Dreamsphere with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Yntec/Dreamsphere with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Yntec/Dreamsphere", 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 vae/diffusion_pytorch_model.fp16.bin from Yntec/Dreamsphere: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/Yntec/Dreamsphere/resolve/refs%2Fpr%2F1/vae/diffusion_pytorch_model.fp16.bin
- Command line
-
hf download hf://Yntec/Dreamsphere@refs/pr/1/vae/diffusion_pytorch_model.fp16.bin
-
curl -L -o diffusion_pytorch_model.fp16.bin https://huggingface.co/Yntec/Dreamsphere/resolve/refs%2Fpr%2F1/vae/diffusion_pytorch_model.fp16.bin
167 MB
- Xet hash:
- f7774223e7fe3064fc37c6c129f94bb9dac8299aab6fd5223f2b43179893afa2
- Size of remote file:
- 167 MB
- SHA256:
- 2d3a3dd7fc20b496975adb81e6d418f04470b0ccaf9cef7428bfb4446144d51c
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