Feature Extraction
sentence-transformers
Safetensors
ONNX
code
bert
code-retrieval
issue-localization
custom_code
text-embeddings-inference
Instructions to use codeusmorbid/jina-v2-code-ft2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use codeusmorbid/jina-v2-code-ft2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("codeusmorbid/jina-v2-code-ft2", 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
Download model.safetensors from codeusmorbid/jina-v2-code-ft2: direct link, hf CLI and curl.
- Browser
- Download file 644 MB
-
https://huggingface.co/codeusmorbid/jina-v2-code-ft2/resolve/main/model.safetensors
- Command line
-
hf download hf://codeusmorbid/jina-v2-code-ft2/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/codeusmorbid/jina-v2-code-ft2/resolve/main/model.safetensors
644 MB
- Xet hash:
- e2dde47517fe5f34498aa0ed64ce63f7a61294906edd25cca851fc4053fb453b
- Size of remote file:
- 644 MB
- SHA256:
- 0fee71d6aac0d36361962c565247bd831ae5323201b2ab3bc04527bc3e4b3d1c
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