Instructions to use b-f/ContinuitySeq-A with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use b-f/ContinuitySeq-A with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("b-f/ContinuitySeq-A", 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
Download text_encoder/pytorch_model.bin from b-f/ContinuitySeq-A: direct link, hf CLI and curl.
- Browser
- Download file 1.36 GB
-
https://huggingface.co/b-f/ContinuitySeq-A/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://b-f/ContinuitySeq-A/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/b-f/ContinuitySeq-A/resolve/main/text_encoder/pytorch_model.bin
1.36 GB
- Xet hash:
- c42866b13afb96eda9bd7f909bdcf9d1448d173f10e71c44a2bcb2c25b90d4e2
- Size of remote file:
- 1.36 GB
- SHA256:
- 34b7b0e54c973d45b6c377acedd433e962c7bf49a75e3b30b402c05547291652
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