Instructions to use 8glabs/test_trained_models_textual_cinematic_style with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use 8glabs/test_trained_models_textual_cinematic_style with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("8glabs/test_trained_models_textual_cinematic_style", 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.bin from 8glabs/test_trained_models_textual_cinematic_style: direct link, hf CLI and curl.
- Browser
- Download file 167 MB
-
https://huggingface.co/8glabs/test_trained_models_textual_cinematic_style/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://8glabs/test_trained_models_textual_cinematic_style/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/8glabs/test_trained_models_textual_cinematic_style/resolve/main/vae/diffusion_pytorch_model.bin
167 MB
- Xet hash:
- 040532a81b590f1df9bd8b3dc91773debfa1623913388a4a4b4d9cea04a4cb47
- Size of remote file:
- 167 MB
- SHA256:
- 472eaaa6ec300b7d29b7b6271624c65d252e2de850cac4ff9575edadeb174cd9
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