Instructions to use sofom/Style-Embedding-m4_extended with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sofom/Style-Embedding-m4_extended with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="sofom/Style-Embedding-m4_extended")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sofom/Style-Embedding-m4_extended") model = AutoModel.from_pretrained("sofom/Style-Embedding-m4_extended") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b4d6d48aecd001ea44b0a4b7b76322e55ca18dda48d8c60316b02588ab403e88
- Size of remote file:
- 249 MB
- SHA256:
- 19442c8ad2139007a87e54f7f84e8204b126352cac17da738e6524bc1629bd06
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