Instructions to use tensorboy/test_embedding_test_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tensorboy/test_embedding_test_1 with Transformers:
# Load model directly from transformers import AutoTokenizer, HF_ColBERT tokenizer = AutoTokenizer.from_pretrained("tensorboy/test_embedding_test_1") model = HF_ColBERT.from_pretrained("tensorboy/test_embedding_test_1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 116e6025ae938b8c7a0473c3fe6ad276f48a86d91305c3860daa76bafb843d4a
- Size of remote file:
- 438 MB
- SHA256:
- 202bb4776718712e30debbf60555dab7f443cd9520fbe7a0b90f0cdfd07cdd2a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.