Instructions to use kejian/cond-lovingly with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kejian/cond-lovingly with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("kejian/cond-lovingly") model = AutoModel.from_pretrained("kejian/cond-lovingly") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 187431a5c94326f8b14d2a5e0ecc4f0a2e921ef7962b17e4942518e25df94bc5
- Size of remote file:
- 457 MB
- SHA256:
- c7ca3382d72e62e3ed9936894afd50e43b4372b63b5f41767dace56cdc68cf71
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