Update README.md

README.md

@@ -39,7 +39,7 @@ This optimization resulted in a **~4x reduction in file size** and significant i
 
 **This is the model intended for direct deployment in mobile applications.**
 
-The original, full-precision (FP32) model can be found at the [main model repository here](https_URL_TO_YOUR_BASE_REPO_). <!--- IMPORTANT: Replace this URL -->
+The original, full-precision (FP32) model can be found at the [main model repository here](https://huggingface.co/SharpWoofer/distilroberta-sms-spam-detector)
 
 ## Model Description
 
@@ -62,7 +62,7 @@ import numpy as np
 import scipy.special
 
 # Load the tokenizer
-tokenizer = AutoTokenizer.from_pretrained("your-hf-username/distilroberta-sms-spam-detector-onnx-quantized") # <-- Replace
+tokenizer = AutoTokenizer.from_pretrained("SharpWoofer/distilroberta-sms-spam-detector-onnx-quantized")
 # Load the ONNX session
 session = ort.InferenceSession("path/to/your/model.quant.onnx")