Instructions to use stablediffusionapi/baka1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use stablediffusionapi/baka1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stablediffusionapi/baka1", 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 stablediffusionapi/baka1: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/stablediffusionapi/baka1/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://stablediffusionapi/baka1/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/stablediffusionapi/baka1/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 0e54f197a723269bcab0b27c33978e9cbf3660f24b0049963cf2d8de1c16ed07
- Size of remote file:
- 492 MB
- SHA256:
- 7602d4f6d7d2cc64a15a01ceaab4464a6c0c50f991f8fc302c345e22a58e9e3e
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