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paraphrase-multilingual-MiniLM-L12-v2-onnx-Q
Qdrant/paraphrase-multilingual-MiniLM-L12-v2-onnx-Q
paraphrase-multilingual-MiniLM-L12-v2-onnx-Q is a sentence similarity model from Qdrant. Use it when you need a score for how close two texts are. It is set up for transformers. The card lists the license as apache-2.0.
Quantized ONNX port of sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2 for text classification and similarity searches.
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At a glance
- Task
- Sentence Similarity
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Jan 16, 2024
- Updated
- Jul 15, 2024
- SHA
- faf4aa42
Model card
From the Hugging Face model README
Quantized ONNX port of sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2 for text classification and similarity searches.
Usage
Here's an example of performing inference using the model with FastEmbed.
from fastembed import TextEmbedding
documents = [
"You should stay, study and sprint.",
"History can only prepare us to be surprised yet again.",
]
model = TextEmbedding(model_name="sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2")
embeddings = list(model.embed(documents))
# [
# array([1.96449570e-02, 1.60677675e-02, 4.10149433e-02...]),
# array([-1.56669170e-02, -1.66313536e-02, -6.84525725e-03...])
# ]
- Task
- Sentence Similarity
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Jan 16, 2024
- Updated
- Jul 15, 2024