Instructions to use kandinskylab/tiny-kandinsky-s2v-modular-pipe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kandinskylab/tiny-kandinsky-s2v-modular-pipe with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kandinskylab/tiny-kandinsky-s2v-modular-pipe", 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 tokenizer/tokenizer.json from kandinskylab/tiny-kandinsky-s2v-modular-pipe: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/kandinskylab/tiny-kandinsky-s2v-modular-pipe/resolve/main/tokenizer/tokenizer.json
- Command line
-
hf download hf://kandinskylab/tiny-kandinsky-s2v-modular-pipe/tokenizer/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/kandinskylab/tiny-kandinsky-s2v-modular-pipe/resolve/main/tokenizer/tokenizer.json
11.4 MB
- Xet hash:
- cd15a6e25b0dc80fe2339154c9db8c712e0bdbe99ab3e3594c990561651d5242
- Size of remote file:
- 11.4 MB
- SHA256:
- 1ab7a851e5c63d5fafbfdac72e3b4a8d08613f6bbb06ee39036fdf870ef59c93
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