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 model.safetensors from vedevpatel/CodeIntel-150M: direct link, hf CLI and curl.
- Browser
- Download file 298 MB
-
https://huggingface.co/vedevpatel/CodeIntel-150M/resolve/main/model.safetensors
- Command line
-
hf download hf://vedevpatel/CodeIntel-150M/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/vedevpatel/CodeIntel-150M/resolve/main/model.safetensors
298 MB
- Xet hash:
- 5ad2c6ce06d8daeff01cbefe5e761bd021bb114f29869469d36fbec0eabcb7bd
- Size of remote file:
- 298 MB
- SHA256:
- 2e91aef7d8d65740516546ed8a0727726f6d03a475b1625f9ac5f0ff09b874e1
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