Instructions to use falca/DreamlabsOil_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use falca/DreamlabsOil_v2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("falca/DreamlabsOil_v2", 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 text_encoder/pytorch_model.bin from falca/DreamlabsOil_v2: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/falca/DreamlabsOil_v2/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://falca/DreamlabsOil_v2/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/falca/DreamlabsOil_v2/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- b085cff0957cd944899eae5fdcebe8618fec8f8ccdc5401ff6d8413ac39cc1f2
- Size of remote file:
- 492 MB
- SHA256:
- 63a6333eebfc6e65a172b25d0b739a8c25eff413b25c8af2394b3453b8c539f7
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