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README.md

@@ -1,15 +1,13 @@
 ---
-license: apache-2.0
+license: mit
 tags:
   - sleep-staging
-  - cardio-respiratory
-  - non-causal
   - wav2sleep
   - polysomnography
   - time-series
   - pytorch
 library_name: wav2sleep
-pipeline_tag: time-series-classification
+pipeline_tag: other
 ---
 
 # wav2sleep
@@ -48,7 +46,7 @@ of physiological signals for sleep staging.
 from wav2sleep import load_model
 
 # Load model from Hugging Face Hub
-model = load_model("wav2sleep")
+model = load_model("hf://joncarter/wav2sleep")
 
 # Or load from local checkpoint
 model = load_model("/path/to/checkpoint")
@@ -59,7 +57,7 @@ For inference on new data:
 ```python
 from wav2sleep import load_model, predict_on_folder
 
-model = load_model("wav2sleep")
+model = load_model("hf://joncarter/wav2sleep")
 predict_on_folder(
     input_folder="/path/to/edf_files",
     output_folder="/path/to/predictions",
@@ -70,7 +68,7 @@ predict_on_folder(
 ## Training Data
 
 The model was trained on polysomnography data from multiple publicly available datasets
-managed by the National Sleep Research Resource (NSRR), including SHHS and MESA.
+managed by the National Sleep Research Resource (NSRR).
 
 ## Citation
 
@@ -87,4 +85,4 @@ managed by the National Sleep Research Resource (NSRR), including SHHS and MESA.
 
 ## License
 
-Apache 2.0
+MIT