Update README.md

README.md

@@ -29,7 +29,7 @@ This segmentation model has been trained on English data (Callhome) using diariz
 ```python
 from diarizers import SegmentationModel
 
-segmentation_model = SegmentationModel().from_pretrained('diarizers-community/speaker-segmentation-fine-tuned-callhome-jpn')
+segmentation_model = SegmentationModel().from_pretrained('foduucom/speaker-segmentation-eng')
 ```
 
 To use it within a pyannote speaker diarization pipeline, load the [pyannote/speaker-diarization-3.1](https://huggingface.co/pyannote/speaker-diarization-3.1) pipeline, and convert the model to a pyannote compatible format: 
@@ -47,7 +47,7 @@ device = torch.device("cuda:0") if torch.cuda.is_available() else torch.device("
 pipeline = Pipeline.from_pretrained("pyannote/speaker-diarization-3.1")
 pipeline.to(device)
 
-model = SegmentationModel().from_pretrained("nehulagrawal/speaker-segmentation-eng")
+model = SegmentationModel().from_pretrained("foduucom/speaker-segmentation-eng")
 model = model.to_pyannote_model()
 pipeline._segmentation.model = model.to(device)
 ```
@@ -87,7 +87,7 @@ device = torch.device("cuda:0") if torch.cuda.is_available() else torch.device("
 pipeline = Pipeline.from_pretrained("pyannote/speaker-diarization-3.1")
 pipeline.to(device)
 
-model = SegmentationModel().from_pretrained("nehulagrawal/speaker-segmentation-eng")
+model = SegmentationModel().from_pretrained("foduucom/speaker-segmentation-eng")
 model = model.to_pyannote_model()
 pipeline._segmentation.model = model.to(device)
 
@@ -131,4 +131,19 @@ The following hyperparameters were used during training:
 - Transformers 4.40.1
 - Pytorch 2.2.1+cu121
 - Datasets 2.19.1
-- Tokenizers 0.19.1
+- Tokenizers 0.19.1
+
+
+
+## Model Card Contact
+
+For inquiries and contributions, please contact us at [email protected].
+
+```bibtex
+@ModelCard{
+  author    = {Nehul Agrawal and
+               Rahul parihar},
+  title     = {{Speaker Diarization in english language},
+  year      = {2023}
+}
+```