Sentence Similarity
sentence-transformers
PyTorch
TensorFlow
JAX
ONNX
Safetensors
OpenVINO
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use sentence-transformers/msmarco-MiniLM-L6-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sentence-transformers/msmarco-MiniLM-L6-v3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sentence-transformers/msmarco-MiniLM-L6-v3") 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/msmarco-MiniLM-L6-v3 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sentence-transformers/msmarco-MiniLM-L6-v3") model = AutoModel.from_pretrained("sentence-transformers/msmarco-MiniLM-L6-v3", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from sentence-transformers/msmarco-MiniLM-L6-v3: direct link, hf CLI and curl.
- Browser
- Download file 91 MB
-
https://huggingface.co/sentence-transformers/msmarco-MiniLM-L6-v3/resolve/main/tf_model.h5
- Command line
-
hf download hf://sentence-transformers/msmarco-MiniLM-L6-v3/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/sentence-transformers/msmarco-MiniLM-L6-v3/resolve/main/tf_model.h5
91 MB
- Xet hash:
- 5922d3a89ee795037073d54b23bf44d184da39b8cf5809a4229ae6d6c6917690
- Size of remote file:
- 91 MB
- SHA256:
- 5f4f194a925d21f972ae6149d1f9a94dae43886a3fff1886977a950c6862fcd9
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