Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
text-embeddings-inference
Instructions to use Kraft102/consulting-embeddings-bge-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Kraft102/consulting-embeddings-bge-large with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Kraft102/consulting-embeddings-bge-large") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cf15b6d95e3a408dcc725949e26f01bbd4a1394604cf9a68eef034aa328982f9
- Size of remote file:
- 1.34 GB
- SHA256:
- a059d5b8b56f4e4da36364f8dd89ce7ddab90d2d01c36dc10522be68769f27be
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.