Update README.md

README.md

@@ -6,33 +6,6 @@ base_model:
 - rhasspy/piper-voices
 pipeline_tag: text-to-audio
 ---
-# Model Card for [Model Name]
+# MikeV3 for Piper Voices
 
-## Model Details
-- **Model Name**: [Your Model Name]
-- **Model Type**: Text-to-Audio
-- **Base Model**: [rhasspy/piper-voices](https://huggingface.co/rhasspy/piper-voices)
-- **Version**: [e.g., v1.0]
-- **License**: Apache-2.0
-- **Developers**: [Your Name or Organization]
-- **Release Date**: [e.g., YYYY-MM-DD]
-- **Contact**: [e.g., email, GitHub, or Hugging Face profile]
-- **Languages**: English (en)
-- **Pipeline Tag**: text-to-audio
-
-## Model Description
-This model is a [brief description, e.g., text-to-audio model designed to generate high-quality audio from textual input]. It is built upon the [rhasspy/piper-voices](https://huggingface.co/rhasspy/piper-voices) base model and fine-tuned for [specific use case or improvements, e.g., improved clarity, multilingual support, or domain-specific audio generation].
-
-- **Intended Use**: [e.g., Generating audio for accessibility, virtual assistants, or content creation]
-- **Primary Users**: [e.g., Developers, researchers, or content creators]
-- **Out-of-Scope Use Cases**: [e.g., Uses not intended, such as generating misleading audio or unethical applications]
-
-## Training Details
-- **Training Data**: [Describe the dataset(s) used, e.g., public datasets, proprietary data, or synthetic data. Include size, source, and any preprocessing steps.]
-- **Training Procedure**: [e.g., Fine-tuning details, epochs, hardware used, training time]
-- **Hyperparameters**: [e.g., Learning rate, batch size, optimizer]
-- **Compute Infrastructure**: [e.g., GPU/TPU type, cloud provider, or local setup]
-
-## Evaluation
-- **Metrics**: [e.g., Mean Opinion Score (MOS), Word Error Rate (WER), or other audio quality metrics]
-- **Results**: [Summarize performance, e
+![Model Demo](https://i.imgur.com/7wAH5yN.gif)