dsadd4/UltraMS-Unsupervised

UltraMS Unsupervised

The general UltraMS MS/MS encoder, released from the completed retention-time-only epoch 11 (rtonly11) training checkpoint. UltraMS learned from UltraMSdata through masked peak reconstruction (MPR), followed by retention-time training. This model returns the encoder's normalized spectrum-level CLS embedding.

Output	Value
Embedding dimension	1024
Maximum spectral peaks	150
Python model name	"unsupervised"
Weights SHA-256	6a4c6660999848c409303119f6caa54fbae9444d0b75c7fcd8bafd303cde9830

python -m pip install ultrams

from ultrams import UltraMS

model = UltraMS.from_pretrained("unsupervised")
embedding = model.encode(
    mz=[100.1, 121.1, 150.0], intensity=[20, 100, 35], precursor_mz=301.2
).embedding
print(embedding.shape)  # (1024,)

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, model selection, and PyTorch fine-tuning example.

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.