| license: apache-2.0 | |
| tags: | |
| - mass-spectrometry | |
| - metabolomics | |
| - spectrum-embedding | |
| # UltraMS Search | |
| The spectrum-to-spectrum contrastive model selected for the UltraAtlas application (`best.pt`). `encode(...).embedding` returns its normalized 512-dimensional projection of the UltraMS encoder's CLS embedding. Use this representation to rank spectra in a supplied reference library by cosine similarity. | |
| | Output | Value | | |
| | --- | --- | | |
| | Embedding dimension | 512 | | |
| | Maximum spectral peaks | 150 | | |
| | Python model name | `"search"` | | |
| | Weights SHA-256 | `447e41e99e5f6ee4155f5dd9938bd7b5fe3f09239b6d5eb0f4973b44c963e383` | | |
| ```bash | |
| python -m pip install ultrams | |
| ``` | |
| ```python | |
| from ultrams import UltraMS | |
| model = UltraMS.from_pretrained("search") | |
| embedding = model.encode( | |
| mz=[100.1, 121.1, 150.0], intensity=[20, 100, 35], precursor_mz=301.2 | |
| ).embedding | |
| print(embedding.shape) # (512,) | |
| ``` | |
| Supply measured spectral peak `m/z` and intensity arrays plus precursor-ion `m/z`. UltraMS requires at least three spectral peaks with positive `m/z`, normalizes intensities by their maximum when positive, and retains the 150 most intense spectral peaks when needed. See the [input format](https://github.com/Dsadd4/UltraMS/blob/main/docs/data-format.md), [model selection](https://github.com/Dsadd4/UltraMS/blob/main/docs/model-selection.md), and [spectrum search example](https://github.com/Dsadd4/UltraMS/blob/main/examples/spectrum_search.py). | |
| Use `return_peaks=True` in `model.encode(...)` to obtain final encoder embeddings aligned with the retained spectral peaks. The three released checkpoints are in the [UltraMS model family](https://huggingface.co/collections/dsadd4/ultrams-6ab4cfaa860cbbd1f9a6b9b6). | |