Sentence Similarity
sentence-transformers
PyTorch
ONNX
Safetensors
OpenVINO
Transformers
English
bert
feature-extraction
text-embeddings-inference
Instructions to use sentence-transformers/all-MiniLM-L12-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sentence-transformers/all-MiniLM-L12-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sentence-transformers/all-MiniLM-L12-v1") 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] - Transformers
How to use sentence-transformers/all-MiniLM-L12-v1 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("sentence-transformers/all-MiniLM-L12-v1", dtype="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Add new SentenceTransformer model with an onnx backend
#13
by tomaarsen HF Staff - opened
- onnx/model.onnx +3 -0
onnx/model.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:0765fcd5407d29fd83483cc8f5cb1b37668449644fde3ad43d41dab8f6e87ec4
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size 133126567
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