Update README.md

README.md

@@ -53,7 +53,7 @@ model = separator.from_hparams(source="speechbrain/sepformer-whamr-enhancement",
 # for custom file, change path
 est_sources = model.separate_file(path='speechbrain/sepformer-whamr-enhancement/example_whamr.wav') 
 
-torchaudio.save("enhanced_whamr.wav", est_sources[:, :, 0].detach().cpu(), 16000)
+torchaudio.save("enhanced_whamr.wav", est_sources[:, :, 0].detach().cpu(), 8000)
 
 ```
 
@@ -61,26 +61,13 @@ torchaudio.save("enhanced_whamr.wav", est_sources[:, :, 0].detach().cpu(), 16000
 To perform inference on the GPU, add  `run_opts={"device":"cuda"}`  when calling the `from_hparams` method.
 
 ### Training
-The model was trained with SpeechBrain (fc2eabb7).
-To train it from scratch follows these steps:
-1. Clone SpeechBrain:
-```bash
-git clone https://github.com/speechbrain/speechbrain/
-```
-2. Install it:
-```
-cd speechbrain
-pip install -r requirements.txt
-pip install -e .
-```
+The training script is currently being worked on an ongoing pull-request. 
+
+We will update the model card as soon as the PR is merged. 
 
-3. Run Training:
-```
-cd  recipes/WHAMandWHAMR/separation/
-python train.py hparams/sepformer-whamr.yaml --data_folder=your_data_folder --sample_rate=16000
 ```
 
-You can find our training results (models, logs, etc) [here](https://drive.google.com/drive/folders/1QiQhp1vi5t4UfNpNETA48_OmPiXnUy8O?usp=sharing).
+You can find our training results (models, logs, etc) [here](https://drive.google.com/drive/folders/1V0KwkEfWwomZ0Vjox0BTnQ694_uxgu8G).
 
 ### Limitations
 The SpeechBrain team does not provide any warranty on the performance achieved by this model when used on other datasets.