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 codeintel_adapter.json from vedevpatel/CodeIntel-150M: direct link, hf CLI and curl.
- Browser
- Download file 191 Bytes
-
https://huggingface.co/vedevpatel/CodeIntel-150M/resolve/main/codeintel_adapter.json
- Command line
-
hf download hf://vedevpatel/CodeIntel-150M/codeintel_adapter.json
-
curl -L -o codeintel_adapter.json https://huggingface.co/vedevpatel/CodeIntel-150M/resolve/main/codeintel_adapter.json
191 Bytes
| { | |
| "pooling": "cls", | |
| "normalize": true, | |
| "query_prefix": "", | |
| "document_prefix": "", | |
| "recommended_max_length": 8192, | |
| "requires_remote_code": false, | |
| "int8_fp32_nodes": "/mlp/Wo/" | |
| } | |