| --- |
| base_model: unknown |
| language: |
| - code |
| library_name: model2vec |
| license: mit |
| model_name: potion-code-16M-v2-onnx |
| tags: |
| - embeddings |
| - static-embeddings |
| - sentence-transformers |
| - onnx |
| --- |
| |
| # potion-code-16M-v2-onnx |
|
|
| This is an ONNX export of the [minishlab/potion-code-16M-v2](https://huggingface.co/minishlab/potion-code-16M-v2) Model2Vec model, produced with the [ONNX](https://onnx.ai/) runtime. [Model2Vec](https://github.com/MinishLab/model2vec) models use static embeddings, allowing text embeddings to be computed orders of magnitude faster on both GPU and CPU. This ONNX export lets you run the model with `onnxruntime` or `transformers.js`, without depending on the `model2vec` package. |
|
|
| `model_quantized.onnx` is int8 quantized for CPU, `model.onnx` is FP32. |
|
|
| ## Usage |
|
|
| ### Using ONNX Runtime |
|
|
| ```python |
| import onnxruntime as ort |
| from transformers import AutoTokenizer |
| |
| tokenizer = AutoTokenizer.from_pretrained("potion-code-16M-v2-onnx") |
| session = ort.InferenceSession("onnx/model_quantized.onnx") # or onnx/model.onnx |
| |
| encodings = tokenizer(["Example sentence"], padding=True, return_tensors="np") |
| embeddings = session.run(None, dict(encodings))[0] |
| ``` |
|
|
| ## Overview |
|
|
| **potion-code-16M-v2** is a fast static code embedding model optimized for code retrieval tasks. It powers [Semble](https://github.com/MinishLab/semble), a code search library for agents. It is distilled from [nomic-ai/CodeRankEmbed](https://huggingface.co/nomic-ai/CodeRankEmbed) and trained on the [CornStack](https://huggingface.co/datasets/nomic-ai/cornstack-python-v1) code corpus using [Tokenlearn](https://github.com/MinishLab/tokenlearn) and contrastive fine-tuning. |
| It is the successor to [potion-code-16M](https://huggingface.co/minishlab/potion-code-16M). |
| It uses static embeddings, allowing text and code embeddings to be computed orders of magnitude faster than transformer-based models on both GPU and CPU. |
|
|
| ## Model Details |
|
|
| | Property | Value | |
| | -------------------- | ---------------------------------------------------------------- | |
| | Parameters | \~16M | |
| | Embedding dimensions | 256 | |
| | Vocabulary size | \~63,500 | |
| | Teacher model | nomic-ai/CodeRankEmbed | |
| | Training corpus | CornStack (6 languages: Python, Java, JavaScript, Go, PHP, Ruby) | |
| | Max sequence length | 1,000,000 tokens (static, no limit in practice) | |
|
|
| ### Further details |
|
|
| See the original model [minishlab/potion-code-16M-v2](https://huggingface.co/minishlab/potion-code-16M-v2) for complete details. |
|
|
