Instructions to use carsonpoole/binary-embeddings with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use carsonpoole/binary-embeddings with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="carsonpoole/binary-embeddings")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("carsonpoole/binary-embeddings") model = AutoModel.from_pretrained("carsonpoole/binary-embeddings", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Upload model
Verified signaturef47a00a -
Upload model
Verified signature420c5fc
-
Upload model
Verified signature4110522 -
Upload model
Verified signatureda3ed40 -
Create 1_Pooling/config.json
Verified signature465d936 -
Upload tokenizer.json
Verified signature5098845 -
Upload tokenizer
Verified signature8ecf1fb -
Upload tokenizer
Verified signatureaf5eddf -
Upload model
Verified signaturee159926 -
initial commit
Verified signaturedadb04e