Sentence Similarity
sentence-transformers
ONNX
Safetensors
English
code
modernbert
feature-extraction
code-search
code-retrieval
bug-localization
Eval Results (legacy)
text-embeddings-inference
Instructions to use vedevpatel/CodeIntel-150M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use vedevpatel/CodeIntel-150M with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("vedevpatel/CodeIntel-150M") 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] - Notebooks
- Google Colab
- Kaggle
Download onnx/model.onnx from vedevpatel/CodeIntel-150M: direct link, hf CLI and curl.
- Browser
- Download file 597 MB
-
https://huggingface.co/vedevpatel/CodeIntel-150M/resolve/main/onnx/model.onnx
- Command line
-
hf download hf://vedevpatel/CodeIntel-150M/onnx/model.onnx
-
curl -L -o model.onnx https://huggingface.co/vedevpatel/CodeIntel-150M/resolve/main/onnx/model.onnx
597 MB
- Xet hash:
- 22d0656d3e88b714ad93e4a68034bbdc769c3d0d02aefc8e45f82a926faca505
- Size of remote file:
- 597 MB
- SHA256:
- 3d15615f9ca440e31e194d377fa1e5fd3c63b17fbd8008b296a4135c6619c909
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