Create README.md

README.md

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+---
+base_model:
+- Qwen/Qwen2.5-Coder-0.5B
+---
+
+<br><br>
+
+<p align="center">
+<img src="https://huggingface.co/datasets/jinaai/documentation-images/resolve/main/logo.webp" alt="Jina AI: Your Search Foundation, Supercharged!" width="150px">
+</p>
+
+<p align="center">
+<b>The code embedding model trained by <a href="https://jina.ai/"><b>Jina AI</b></a>.</b>
+</p>
+
+# Jina Embeddings c1: A Small but Performant Code Embedding Model
+
+## Intended Usage & Model Info
+`jina-embeddings-c1` is an embedding model for code retrieval. 
+The model supports natural language-to-code, code-to-code, and code-to-natural language retrieval across 15+ programming languages. 
+
+
+Built on [Qwen/Qwen2.5-Coder-0.5B](https://huggingface.co/Qwen/Qwen2.5-Coder-0.5B), `jina-embeddings-c1` features:
+
+- **Multilingual support** (15+ programming languages) and compatibility with a wide range of domains, including web development, machine learning, [...].
+- **Task-specific instruction prefixes** for NL2Code, Code2Code, Code2NL, Technical QA, and Code2Completion retrieval, which can be selected at inference time.
+- **Flexible embedding size**: dense embeddings are 896-dimensional by default but can be truncated to as low as 64 with minimal performance loss.
+
+
+Summary of features:
+
+| Feature   | Jina Embeddings C1   |
+|------------|------------|
+| Base Model | Qwen2.5-Coder-0.5B |
+| Supported Tasks | `nl2code`, `code2code`, `code2nl`, `qa`, `code2completion` |
+| Model DType | BFloat 16 |
+| Max Sequence Length | 32768 |
+| Embedding Vector Dimension | 896 |
+| Matryoshka dimensions | 64, 128, 256, 512, 896 |
+| Pooling Strategy | Last-token pooling |
+| Attention Mechanism | FlashAttention2 |
+
+
+
+## Training & Evaluation
+
+Please refer to our technical report of jina-embeddings-c1 for training details and benchmarks.
+
+## Contact
+
+Join our [Discord community](https://discord.jina.ai) and chat with other community members about ideas.
+```