Sentence Similarity
sentence-transformers
PyTorch
ONNX
Safetensors
OpenVINO
English
bert
mteb
Sentence Transformers
Eval Results (legacy)
text-embeddings-inference
Instructions to use thenlper/gte-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use thenlper/gte-large with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("thenlper/gte-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] - Inference
- Notebooks
- Google Colab
- Kaggle
Error while loading model
#19
by iabhishekofficial - opened
#Code
from sentence_transformers import SentenceTransformer
model = SentenceTransformer('thenlper/gte-large')
sentences = ["This is an example sentence", "Each sentence is converted"]
embeddings = model.encode(sentences)
print(embeddings.shape)
#version
Python version: 3.11.5 (tags/v3.11.5:cce6ba9, Aug 24 2023, 14:38:34) [MSC v.1936 64 bit (AMD64)]
PyTorch version: 2.2.1+cpu
#Error
RuntimeError: Failed to import transformers.models.bert.modeling_bert because of the following error (look up to see its traceback):
Failed to import transformers.integrations.peft because of the following error (look up to see its traceback):
cannot import name '_data_ptr_allocated' from 'torch.distributed.utils'