Instructions to use tensorboy/test_embedding_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tensorboy/test_embedding_test with Transformers:
# Load model directly from transformers import AutoTokenizer, HF_ColBERT tokenizer = AutoTokenizer.from_pretrained("tensorboy/test_embedding_test") model = HF_ColBERT.from_pretrained("tensorboy/test_embedding_test") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 68eefa8155da6be66319423241225a87096268b49b12465638bda9479df2b85d
- Size of remote file:
- 438 MB
- SHA256:
- 2e78ae296a8cc3e2941f10ead8efa8a6caacb67e11588949e916a94296f4ef8f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.