Update README.md

README.md

@@ -125,3 +125,90 @@ configs:
   - split: NanoCodeSearchNetRuby
     path: queries/NanoCodeSearchNetRuby-*
 ---
+
+
+# NanoCodeSearchNet
+
+A tiny, evaluation-ready slice of CodeSearchNet that mirrors the spirit of [NanoBEIR](https://huggingface.co/collections/zeta-alpha-ai/nanobeir): same task, same style, but dramatically smaller so you can iterate and benchmark in minutes instead of hours.
+
+Evaluation can be performed during and after training by integrating with Sentence Transformer's Evaluation module (InformationRetrievalEvaluator).
+
+## NanoCodeSearchNet Evaluation (NDCG@10)
+
+| Model | Avg | Go | Java | JavaScript | PHP | Python | Ruby |
+|---|---:|---:|---:|---:|---:|---:|---:|
+| [multilingual-e5-small](https://huggingface.co/intfloat/multilingual-e5-small) | **0.7351** | 0.6706 | 0.7899 | 0.6582 | 0.6651 | 0.9258 | 0.7008 |
+| [multilingual-e5-large](https://huggingface.co/intfloat/multilingual-e5-large) | **0.7769** | 0.7459 | 0.8304 | 0.7016 | 0.7069 | 0.9513 | 0.7251 |
+| [e5-small-v2](https://huggingface.co/intfloat/e5-small-v2) | **0.7371** | 0.7137 | 0.7758 | 0.6126 | 0.6561 | 0.9582 | 0.7060 |
+| [e5-large-v2](https://huggingface.co/intfloat/e5-large-v2) | **0.7541** | 0.7097 | 0.8124 | 0.6715 | 0.7065 | 0.9386 | 0.6860 |
+| [bge-m3](https://huggingface.co/BAAI/bge-m3) | **0.7094** | 0.6680 | 0.7050 | 0.6154 | 0.6238 | 0.9779 | 0.6662 |
+| [gte-multilingual-base](https://huggingface.co/Alibaba-NLP/gte-multilingual-base) | **0.8112** | 0.7789 | 0.8666 | 0.7344 | 0.7991 | 0.9652 | 0.7231 |
+| [nomic-embed-text-v2-moe](https://huggingface.co/nomic-ai/nomic-embed-text-v2-moe) | **0.7824** | 0.7635 | 0.8343 | 0.6519 | 0.7470 | 0.9852 | 0.7122 |
+| [paraphrase-multilingual-MiniLM-L12-v2](https://huggingface.co/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2) | **0.4651** | 0.3978 | 0.4608 | 0.3269 | 0.2183 | 0.9236 | 0.4631 |
+
+Notes:
+- The above results were computed with `nano_code_search_net_eval.py`.
+
+## What this dataset is
+
+- A collection of 6 programming-language subsets (`corpus`, `queries`, `qrels`) published on the Hugging Face Hub under `hotchpotch/NanoCodeSearchNet`.
+- Each subset contains **50 test queries** and a **corpus of up to 10,000 code snippets**.
+- Queries are function docstrings, and positives are the corresponding function bodies from the same source row.
+- Query IDs are `q-<docid>`, where `docid` is the `func_code_url` when available.
+- Built from the CodeSearchNet `test` split (`refs/convert/parquet`) with deterministic sampling (seed=42).
+- License: **Other** (see CodeSearchNet and upstream repository licenses).
+
+## Subset names
+
+- Split names:
+  - `NanoCodeSearchNetGo`
+  - `NanoCodeSearchNetJava`
+  - `NanoCodeSearchNetJavaScript`
+  - `NanoCodeSearchNetPHP`
+  - `NanoCodeSearchNetPython`
+  - `NanoCodeSearchNetRuby`
+- Config names: `corpus`, `queries`, `qrels`
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+split = "NanoCodeSearchNetPython"
+queries = load_dataset("hotchpotch/NanoCodeSearchNet", "queries", split=split)
+corpus  = load_dataset("hotchpotch/NanoCodeSearchNet", "corpus",  split=split)
+qrels   = load_dataset("hotchpotch/NanoCodeSearchNet", "qrels",   split=split)
+
+print(queries[0]["text"])
+```
+
+### Example eval code
+
+```bash
+python ./nano_code_search_net_eval.py \
+  --model-path intfloat/multilingual-e5-small \
+  --query-prompt "query: " \
+  --corpus-prompt "passage: "
+```
+
+For models that require `trust_remote_code`, add `--trust-remote-code` (e.g., `BAAI/bge-m3`).
+
+## Why Nano?
+
+- **Fast eval loops**: 50 queries × 10k docs fits comfortably on a single GPU/CPU run.
+- **Reproducible**: deterministic sampling and stable IDs.
+- **Drop-in**: BEIR/NanoBEIR-style schemas, so existing IR loaders need minimal tweaks.
+
+### Upstream sources
+
+- Original data: **CodeSearchNet** — *CodeSearchNet Challenge: Evaluating the State of Semantic Code Search* (arXiv:1909.09436).
+- Base dataset: [code-search-net/code_search_net](https://huggingface.co/datasets/code-search-net/code_search_net) (Hugging Face Hub).
+- Inspiration: **NanoBEIR** (lightweight evaluation subsets).
+
+## License
+
+Other. This dataset is derived from CodeSearchNet and ultimately from open-source GitHub repositories. Please respect original repository licenses and attribution requirements.
+
+## Author
+
+- Yuichi Tateno