Instructions to use sofom/Style-Embedding-multisocial with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sofom/Style-Embedding-multisocial with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="sofom/Style-Embedding-multisocial")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sofom/Style-Embedding-multisocial") model = AutoModel.from_pretrained("sofom/Style-Embedding-multisocial", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7207cce2981aa7a97bb287b6fa8d99ad5c5389a3dfae9f6ae4408437706870d8
- Size of remote file:
- 249 MB
- SHA256:
- 670d3d108b0553ba17c0b2e4fe39664996ef7f885bfb5ae7f5f5ce57fbba7bd7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.