Update README.md

README.md

@@ -15,6 +15,7 @@ tags:
 - chemistry
 datasets:
 - roman-bushuiev/GeMS
+- roman-bushuiev/MassSpecGym
 metrics:
 - hit@k
 - cosine_similarity
@@ -24,6 +25,8 @@ metrics:
 
 # NexaMass-V3-Struct
 
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+![nexamass_inference_density_atlas_scaling](https://cdn-uploads.huggingface.co/production/uploads/6643ee570c34964ea12d8bd9/_TrclJb8JyjuhlFG0heH_.png)
 `NexaMass-V3-Struct` is a compact MS/MS spectral encoder for structure-aware representation learning and candidate-bank molecular inference. It maps tandem mass spectra into a learned spectral embedding and predicts RDKit Morgan fingerprint probabilities that can be compared against candidate molecular fingerprints. The model is intended for spectrum embedding, candidate narrowing, structure-aware retrieval research, and confidence/abstention experiments. It is not a de novo molecule generator and should not be used as a standalone top-1 molecular identifier.
 
 The model was developed as part of the Nexa MS/MS pipeline. The foundation checkpoint, `NexaMass-V3`, was trained as a self-supervised spectral encoder over an approximately 201M-spectrum phase-1 campaign. The structure-aligned checkpoint, `NexaMass-V3-Struct`, adapts that encoder to a corrected labeled surface with real RDKit Morgan fingerprint targets. The main finding is that a small encoder can carry useful structure signal and support candidate-bank narrowing, while exact local ranking and calibrated confidence remain separate downstream problems.
@@ -34,6 +37,9 @@ The model was developed as part of the Nexa MS/MS pipeline. The foundation check
 
 The model contains a spectral transformer backbone, an SSL projection head, a Morgan fingerprint structure head, a spectrum-side retrieval query projection, a fingerprint-side target projection, and experimental retrieval/reranking heads. The strongest current inference surface is the Morgan fingerprint prediction and candidate-bank decode path. The trained retrieval projection is included for research, but it is not promoted as a reliable final decision layer.
 
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+![nexamass_encoder_architecture](https://cdn-uploads.huggingface.co/production/uploads/6643ee570c34964ea12d8bd9/N_KySKnB-St8bztjoujfr.png)
+
 ## Intended Use
 
 Use this model to embed MS/MS spectra, build nearest-neighbor or clustering analyses, predict Morgan fingerprint probability vectors from spectra, score spectra against candidate banks, inspect structure-family neighborhoods, and develop ranking or confidence adapters over a frozen spectral encoder. The model is also suitable for research into structure-aware MS/MS representation learning and candidate narrowing.
@@ -82,7 +88,3 @@ MS/MS structure inference can affect downstream scientific interpretation. Users
 ## Citation
 
 If you use this model, cite the NexaMass project release and the accompanying technical report when available. Relevant background work includes DreaMS for self-supervised MS/MS representation learning, MassSpecGym for benchmark framing, CSI:FingerID for fingerprint-mediated candidate search, and related spectra-structure retrieval and de novo generation systems such as MIST, MSNovelist, CMSSP, CSU-MS2, MSBERT, Spec2Mol, and MS2Mol.
-
-## Recommended Name
-
-Use `NexaMass-V3` for the promoted self-supervised foundation encoder and `NexaMass-V3-Struct` for the RDKit/Morgan-aligned checkpoint. Use `NexaMass-Atlas` for future indexed candidate-bank inference systems built on top of this encoder.