Update README.md

README.md

@@ -12,7 +12,7 @@ datasets:
 # Model Card for Model ID
 Voicera is a AR text-to-speech model trained on ~1000hrs of speech data.
 speech is converted to discrete tokens using "Multi-Scale Neural Audio Codec (SNAC)" model
-NB: This is not a SOTA model, and not accuarate enough for production usecase
+**NB: This is not a SOTA model, and not accuarate enough for production usecase**
 
 
 
@@ -29,7 +29,7 @@ It's a project to explore TTS technology and improve audio output quality.
 
 
 - **Developed by:** Lwasinam Dilli
-- **Funded by [optional]:** Lwasinam Dilli
+- **Funded by :** Lwasinam Dilli
 - **Model type:** GPT2-Transformer architecture
 - **License:** Free and Open to use I guess :)
 
@@ -40,7 +40,7 @@ It's a project to explore TTS technology and improve audio output quality.
 
 - **Repository:** [More Information Needed]
 - **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **Demo :** [Demos](https://lwasinam.github.io/)
 
 
 
@@ -79,7 +79,7 @@ Hugging Face had pretty much all the datasets I needed. I just had to filter out
 I should probably work on this, the loss went down and the output got better :)
 
 ### Results
- Check out the demo page her -> [Demo]()
+ Check out the demo page her -> [Demo](https://lwasinam.github.io/)
 
 #### Summary