Update README.md

README.md

@@ -4,4 +4,268 @@ pipeline_tag: text-to-speech
 tags:
 - voice
 - speech
----
+- text-to-speech
+- audio
+---
+
+<p align="center">
+  <img alt="Continue-TTS" src="https://github.com/SVECTOR-CORPORATION/Continue-TTS/blob/main/continue-tts-image-banner.jpg?raw=true" width="800">
+</p>
+
+# Continue-TTS
+
+### Text-to-Speech Model Based on Continue-1-OSS
+
+<div align="left" style="line-height: 1;">
+  <a href="https://spec-chat.tech" target="_blank" style="margin: 2px;">
+    <img alt="SVECTOR" src="https://img.shields.io/badge/💬%20Spec%20Chat-Spec%20Chat-blue?style=plastic" style="display: inline-block; vertical-align: middle;"/>
+  </a>
+  
+  <a href="https://huggingface.co/SVECTOR-CORPORATION" target="_blank" style="margin: 2px;">
+    <img alt="SVECTOR" src="https://img.shields.io/badge/🤗%20Hugging%20Face-SVECTOR-536af5?color=536af5&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
+  </a>
+  
+  <a href="https://huggingface.co/SVECTOR-CORPORATION/Continue-TTS/blob/main/LICENSE" style="margin: 2px;">
+    <img alt="License" src="https://img.shields.io/badge/License-Apache%202.0-blue?color=1e88e5&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
+  </a>
+  
+  <a href="https://github.com/SVECTOR-CORPORATION/Continue-TTS" target="_blank" style="margin: 2px;">
+    <img alt="GitHub" src="https://img.shields.io/badge/GitHub-Continue--TTS-181717?logo=github&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
+  </a>
+</div>
+
+## Introduction
+
+We are thrilled to introduce **Continue-TTS**, a fine-tuned text-to-speech model based on the **Continue-1-OSS** architecture, developed by SVECTOR. This model is specifically trained for high-quality speech synthesis and delivers exceptional voice generation capabilities.
+
+**Continue-TTS** is engineered to provide:
+
+- **Natural Speech:** Human-like intonation, emotion, and rhythm that rivals commercial solutions
+- **8 Unique Voices:** Diverse voice options with distinct personalities and characteristics
+- **Real-time Generation:** Low-latency streaming for interactive applications (~200ms)
+- **Emotional Expression:** Built-in support for laughter, sighs, gasps, and other natural emotions
+- **Open Source:** Fully accessible under Apache 2.0 license for research and commercial use
+
+This model is based on the **Continue-1-OSS** architecture and combines the power of large language models with neural audio codecs to generate exceptionally natural speech from text.
+
+### Model Specifications
+
+- **Base Architecture:** Continue-1-OSS
+- **Type:** Text-to-Speech (TTS) Model
+- **Parameters:** 3 Billion
+- **Audio Codec:** SNAC (24kHz)
+- **Context Length:** 131,072 tokens
+- **Vocabulary:** 156,940 tokens (including 28,672 audio tokens)
+- **License:** Apache 2.0
+- **Voices:** 8 (Nova, Aurora, Stellar, Atlas, Orion, Luna, Phoenix, Ember)
+
+## Requirements
+
+To use Continue-TTS, install the required dependencies:
+
+```bash
+pip install transformers torch
+pip install snac  # Audio codec
+pip install vllm==0.7.3  # For fast inference (optional but recommended)
+```
+
+## Quickstart
+
+### Basic Usage
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+model_id = "SVECTOR-CORPORATION/Continue-TTS"
+
+# Load model and tokenizer
+tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+    trust_remote_code=True
+)
+
+# Prepare text with voice
+text = "Hello! I am Continue-TTS, a text-to-speech model based on Continue-1-OSS."
+voice = "nova"  # Choose: nova, aurora, stellar, atlas, orion, luna, phoenix, ember
+
+# Format prompt (TTS format)
+adapted_prompt = f"{voice}: {text}"
+prompt_tokens = tokenizer(adapted_prompt, return_tensors="pt")
+start_token = torch.tensor([[128259]], dtype=torch.int64)
+end_tokens = torch.tensor([[128009, 128260, 128261, 128257]], dtype=torch.int64)
+input_ids = torch.cat([start_token, prompt_tokens.input_ids, end_tokens], dim=1)
+
+# Generate audio tokens
+outputs = model.generate(
+    input_ids.to(model.device),
+    max_new_tokens=1200,
+    temperature=0.6,
+    top_p=0.8,
+    repetition_penalty=1.3,
+    eos_token_id=49158,  # TTS stop token
+    do_sample=True
+)
+
+# Decode tokens (audio codes can be decoded using SNAC decoder)
+generated_tokens = tokenizer.decode(outputs[0], skip_special_tokens=False)
+```
+
+### Using Continue-TTS Package (Recommended)
+
+For easier usage with audio generation, use the Continue-TTS package:
+
+```bash
+pip install continue-speech
+```
+
+```python
+from continue_tts import Continue1Model
+import wave
+
+# Initialize model
+model = Continue1Model(model_name="SVECTOR-CORPORATION/Continue-TTS", max_model_len=2048)
+
+# Generate speech
+text = "Welcome to Continue-TTS! This model is built on Continue-1-OSS."
+audio_chunks = model.generate_speech(prompt=text, voice="nova")
+
+# Save to file
+with wave.open("output.wav", "wb") as wf:
+    wf.setnchannels(1)
+    wf.setsampwidth(2)
+    wf.setframerate(24000)
+    for chunk in audio_chunks:
+        wf.writeframes(chunk)
+```
+
+## Available Voices
+
+Continue-TTS includes 8 professionally designed voices:
+
+| Voice | Gender | Description |
+|-------|--------|-------------|
+| **nova** | Female | Conversational and natural, perfect for general use |
+| **aurora** | Female | Warm and friendly, excellent for storytelling |
+| **stellar** | Female | Energetic and bright, great for upbeat content |
+| **atlas** | Male | Deep and authoritative, ideal for narration |
+| **orion** | Male | Friendly and casual, perfect for conversational content |
+| **luna** | Female | Soft and gentle, excellent for calm narration |
+| **phoenix** | Male | Dynamic and expressive, great for engaging content |
+| **ember** | Female | Warm and engaging, perfect for emotional expression |
+
+## Advanced Features
+
+### Emotion Tags
+
+Add natural emotions to your speech:
+
+```python
+text = "This is incredible! <laugh> I can't believe how natural it sounds. <gasp>"
+```
+
+**Supported emotions:**
+- `<laugh>` - Natural laughter
+- `<chuckle>` - Light laugh
+- `<sigh>` - Expressive sigh
+- `<gasp>` - Surprised gasp
+- `<cough>` - Cough sound
+- `<yawn>` - Yawn
+- `<groan>` - Groan
+- `<sniffle>` - Sniffle
+
+### Custom Generation Parameters
+
+Fine-tune generation quality:
+
+```python
+audio = model.generate_speech(
+    prompt="Your text here",
+    voice="nova",
+    temperature=0.6,        # Lower = more consistent, Higher = more varied
+    top_p=0.8,             # Nucleus sampling threshold
+    max_tokens=1200,       # Maximum audio length
+    repetition_penalty=1.3 # Prevent token repetition
+)
+```
+
+## Use Cases
+
+Continue-TTS excels at:
+
+- **Audiobook Narration:** Natural storytelling with emotional expression
+- **Virtual Assistants:** Conversational AI with personality
+- **Accessibility:** Text-to-speech for visually impaired users
+- **Content Creation:** Voiceovers for videos, podcasts, and presentations
+- **Gaming:** Dynamic character voices and dialogue
+- **Education:** Interactive learning materials with voice
+- **Customer Service:** Natural-sounding automated responses
+
+## Performance
+
+- **Quality:** State-of-the-art natural speech synthesis
+- **Latency:** ~200ms for streaming generation (GPU)
+- **Speed:** Real-time on GPU, slower on CPU
+- **Memory:** ~7GB GPU RAM (FP16), ~14GB (FP32)
+- **Sample Rate:** 24kHz (high quality audio)
+
+## Model Architecture
+
+Continue-TTS is built on the Continue-1-OSS and combines:
+- **Base Model:** Continue-1-OSS (LLaMA-based, 3.3B parameters)
+- **Audio Codec:** SNAC multi-scale neural audio codec
+- **Token Structure:** 7 audio tokens per frame (hierarchical encoding)
+- **Training:** Fine-tuned on few hours of diverse speech data
+
+The model generates audio tokens autoregressively, which are then decoded into waveforms using the SNAC neural codec.
+
+## Training
+
+Continue-TTS was fine-tuned on the Continue-1-OSS using:
+- High-quality speech datasets covering diverse accents and styles
+- Multi-speaker recordings for voice diversity
+- Emotional speech data for expressive synthesis
+- Conversational and narrative content
+
+Training utilized:
+- Continue-1-OSS as base
+- Custom tokenizer with 28,672 audio tokens
+- Multi-stage training (pretraining + fine-tuning)
+- Optimized for naturalness and emotion
+
+## Limitations
+
+As with any TTS model, Continue-TTS has certain limitations:
+
+- **Pronunciation:** May struggle with unusual names, technical terms, or non-English words
+- **Consistency:** Long-form generation may have minor quality variations
+- **Accents:** Primarily trained on specific accent patterns
+- **Compute:** Requires GPU for real-time generation (CPU is slower)
+- **Language:** Currently optimized for English
+
+## Ethical Considerations
+
+SVECTOR is committed to responsible AI development. Users should:
+
+- **Transparency:** Disclose when audio is AI-generated
+- **Consent:** Do not clone voices without explicit permission
+- **Verification:** Implement safeguards against deepfakes and misinformation
+- **Attribution:** Credit the model when used in public projects
+- **Responsible Use:** Avoid generating harmful, deceptive, or illegal content
+
+## License
+
+This model is released under the **Apache License 2.0**. See the [LICENSE](https://huggingface.co/SVECTOR-CORPORATION/Continue-TTS/blob/main/LICENSE) file for complete details.
+
+## Acknowledgments
+
+Continue-1-OSS builds upon advances in neural speech synthesis, large language models, and neural audio codecs. We thank the open-source community for their contributions to these foundational technologies.
+
+---
+
+<p align="center">
+    <i>Developed by <a href="https://www.svector.co.in">SVECTOR</a></i>
+</p>