Instructions to use TitanML/jina-v2-code-embed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TitanML/jina-v2-code-embed with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("TitanML/jina-v2-code-embed", trust_remote_code=True) model = AutoModel.from_pretrained("TitanML/jina-v2-code-embed", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 77357a95afaf3a6e0347a90d8f1de401bb00c2c48363d9772e245df562f1299d
- Size of remote file:
- 641 MB
- SHA256:
- d1d91ddd6987ad85eb970b885111ef41b0a709f51b8aba4569f212d02e7272b6
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