Instructions to use iampanda/zpoint_large_embedding_zh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use iampanda/zpoint_large_embedding_zh with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("iampanda/zpoint_large_embedding_zh") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Add exported onnx model 'model.onnx'
#13
by XudongLiu - opened
Hello!
This pull request has been automatically generated from the Sentence Transformers backend-export Space.
Pull Request overview
- Add exported ONNX model
model.onnx.
Tip:
Consider testing this pull request before merging by loading the model from this PR with the revision argument:
from sentence_transformers import SentenceTransformer
# TODO: Fill in the PR number
pr_number = 2
model = SentenceTransformer(
"iampanda/zpoint_large_embedding_zh",
revision=f"refs/pr/{pr_number}",
backend="onnx",
)
# Verify that everything works as expected
embeddings = model.encode(["The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium."])
print(embeddings.shape)
similarities = model.similarity(embeddings, embeddings)
print(similarities)