Instructions to use carsonpoole/binary-embeddings-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use carsonpoole/binary-embeddings-medium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="carsonpoole/binary-embeddings-medium")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("carsonpoole/binary-embeddings-medium") model = AutoModel.from_pretrained("carsonpoole/binary-embeddings-medium") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ea66eb845e2f3234bbf7859c714190c718e4e870a4aab83295a937b6a82a06f1
- Size of remote file:
- 669 MB
- SHA256:
- 31940ea2c718c00249c014972974fe51b1a79af1a1b8a2a2967c95fbf509f7f2
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