Sentence Similarity
sentence-transformers
PyTorch
ONNX
Safetensors
OpenVINO
English
bert
mteb
Sentence Transformers
Eval Results (legacy)
text-embeddings-inference
Instructions to use thenlper/gte-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use thenlper/gte-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("thenlper/gte-base") 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] - Inference
- Notebooks
- Google Colab
- Kaggle
Add LICENSE file
#16 opened 6 months ago
by
jewittje
Availability on API
#7 opened over 2 years ago
by
DataPhreak
Training scripts
#6 opened over 2 years ago
by
baltachev
Device Map Auto not supported and Is there any way to increase the length of input sequence ????
2
#5 opened over 2 years ago
by
ideepankarsharma2003
"Some weights of BertForSequenceClassification were not initialized" warning when using with sentence_transformer
➕ 1
#3 opened almost 3 years ago
by
HyunggyuJang
Code Search Support
❤️ 1
2
#1 opened almost 3 years ago
by
kevinlu1248