Add pipeline tag and link to paper

README.md

@@ -1,20 +1,23 @@
 ---
+library_name: pytorch
 license: apache-2.0
+pipeline_tag: feature-extraction
 tags:
-  - physiowave
-  - physiowave-t
-  - foundation-model
-  - ecg
-  - electrocardiogram
-  - biosignal
-  - self-supervised
-  - masked-autoencoder
-  - pretrained
-library_name: pytorch
+- physiowave
+- physiowave-t
+- foundation-model
+- ecg
+- electrocardiogram
+- biosignal
+- self-supervised
+- masked-autoencoder
+- pretrained
 ---
 
 # PhysioWave-T-ECG: multi-route pretrained ECG encoder
 
+This model is described in the paper [PhysioWave-T: Token-Efficient Wavelet Foundation Models for Biosignals](https://huggingface.co/papers/2611.08969).
+
 One of the three **PhysioWave-T** encoders ([EEG](https://huggingface.co/ForeverBlue/EEG), ECG, [sEMG](https://huggingface.co/ForeverBlue/EMG)); the [RALF fusion model](https://huggingface.co/ForeverBlue/RALF-SeizeIT2) combines them. Code: <https://github.com/ForeverBlue816/PhysioWave>.
 
 Masked dual-reconstruction pretraining on 12-lead and single-lead ECG. One shared transformer serves two lead configurations through route-specific wavelet frontends, and lead identity enters as a learned embedding of the lead NAME rather than of its index.
@@ -223,4 +226,4 @@ Code: <https://github.com/ForeverBlue816/PhysioWave>
 
 ---
 Prepared by `scripts/prepare_hf_release.py` from `pretrain_ecg_c1_moe`
-on 2026-10-29.
+on 2026-10-29.