Instructions to use LivBigStar/stablediffusion_musinsa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LivBigStar/stablediffusion_musinsa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="LivBigStar/stablediffusion_musinsa")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("LivBigStar/stablediffusion_musinsa") model = AutoModel.from_pretrained("LivBigStar/stablediffusion_musinsa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4d5be323bf8b8aba1d813b5036c7fdfddf7419689598ec1ed391bf719e5ca746
- Size of remote file:
- 1.36 GB
- SHA256:
- 7c2245b80fc1e76f419a81eb71fd517b782221773addc55f647eb54153b376ee
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