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
| { | |
| "__version__": { | |
| "sentence_transformers": "3.0.0", | |
| "transformers": "4.37.2", | |
| "pytorch": "2.2.0+cu121" | |
| }, | |
| "prompts": {}, | |
| "default_prompt_name": null, | |
| "similarity_fn_name": null | |
| } |