Sentence Similarity
sentence-transformers
PyTorch
TensorFlow
Rust
Safetensors
Transformers
English
bert
feature-extraction
text-embeddings-inference
Instructions to use PIXMELT/all-MiniLM-L6-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use PIXMELT/all-MiniLM-L6-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("PIXMELT/all-MiniLM-L6-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] - Transformers
How to use PIXMELT/all-MiniLM-L6-v2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("PIXMELT/all-MiniLM-L6-v2") model = AutoModel.from_pretrained("PIXMELT/all-MiniLM-L6-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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spelling corrections (#13)
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Adding `safetensors` variant of this model (#53)
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Several small spelling errors in README (#48)
Verified signature- Several small spelling errors in README (2f3b461246cd6b756de7c85150aabebbb2c36905) Co-authored-by: Joel Wigton <joelwigton@users.noreply.huggingface.co>44eb404
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Update Sentence Transformers metadata (#46)
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Fix metadata error (#4)
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Rust weights addition (#5)
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