Sentence Similarity
sentence-transformers
Safetensors
nomic_bert
code-search
mteb
custom_code
text-embeddings-inference
Instructions to use madhurr382/coderankembed-apps-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use madhurr382/coderankembed-apps-ft with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("madhurr382/coderankembed-apps-ft", trust_remote_code=True) 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 config_sentence_transformers.json from madhurr382/coderankembed-apps-ft: direct link, hf CLI and curl.
- Browser
- Download file 333 Bytes
-
https://huggingface.co/madhurr382/coderankembed-apps-ft/resolve/main/config_sentence_transformers.json
- Command line
-
hf download hf://madhurr382/coderankembed-apps-ft/config_sentence_transformers.json
-
curl -L -o config_sentence_transformers.json https://huggingface.co/madhurr382/coderankembed-apps-ft/resolve/main/config_sentence_transformers.json
333 Bytes
| { | |
| "__version__": { | |
| "pytorch": "2.10.0+cu128", | |
| "sentence_transformers": "6.1.0", | |
| "transformers": "5.0.0" | |
| }, | |
| "default_prompt_name": null, | |
| "model_type": "SentenceTransformer", | |
| "prompts": { | |
| "document": "", | |
| "query": "Represent this query for searching relevant code: " | |
| }, | |
| "similarity_fn_name": "cosine" | |
| } |