Sentence Similarity
sentence-transformers
Safetensors
mistralbidirectional
swe-bench
code-similarity
code-retrieval
code-search
code-explanation
custom_code
Instructions to use nvidia/NV-EmbedCode-7b-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use nvidia/NV-EmbedCode-7b-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("nvidia/NV-EmbedCode-7b-v1", trust_remote_code=True) 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
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README.md
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- sentence-transformers
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- sentence-similarity
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widget: []
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license: other
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license_name: nvidia-ai-foundation-models-community-license-agreement
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license_link: https://developer.nvidia.com/downloads/ai-foundation-models-license
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- sentence-transformers
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- sentence-similarity
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widget: []
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paper: https://openreview.net/forum?id=k6p8UKRdH7
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license: other
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license_name: nvidia-ai-foundation-models-community-license-agreement
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license_link: https://developer.nvidia.com/downloads/ai-foundation-models-license
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