Instructions to use albburtsev/faucet-v2-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use albburtsev/faucet-v2-1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("albburtsev/faucet-v2-1", 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 albburtsev/faucet-v2-1: direct link, hf CLI and curl.
- Browser
- Download file 681 MB
-
https://huggingface.co/albburtsev/faucet-v2-1/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://albburtsev/faucet-v2-1/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/albburtsev/faucet-v2-1/resolve/main/text_encoder/pytorch_model.bin
681 MB
- Xet hash:
- 2536c2484162bd5243dd00822769d6e003a14a76a46906bbc39593a9de66155e
- Size of remote file:
- 681 MB
- SHA256:
- 05c3e1a6802f613b79cfb17f8b3cdc955704b97d40fbdac4d96c2d54747db7bd
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