Instructions to use carsonpoole/binary-embeddings-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use carsonpoole/binary-embeddings-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="carsonpoole/binary-embeddings-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("carsonpoole/binary-embeddings-base") model = AutoModel.from_pretrained("carsonpoole/binary-embeddings-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ea411db7820129145bb5606242507d99b09603bb1d2d30edb64f6bd1dfb9403c
- Size of remote file:
- 218 MB
- SHA256:
- 894a413759a5ec808de4dbd25fb0c84fe16d8e0c19d58f8ccdb5f4ebeec25584
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