Sentence Similarity
sentence-transformers
PyTorch
ONNX
Safetensors
OpenVINO
English
bert
mteb
Sentence Transformers
Eval Results (legacy)
text-embeddings-inference
Instructions to use intfloat/e5-base-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use intfloat/e5-base-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("intfloat/e5-base-v2") 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
which settings can make the intfloat/e5-base-v2 using GPU?
#8
by WeiZhenKun - opened
ml.g5.xlarge is used on aws sagemaker, but it seems that intfloat/e5-base-v2 does not use the GPU to generate embddings?
Simply move the model to the GPU device like all other models.
model.cuda()
# Then you can generate the embeddings
ok, thanks
WeiZhenKun changed discussion status to closed