Instructions to use OEvortex/TTS-OLD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OEvortex/TTS-OLD with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="OEvortex/TTS-OLD")# Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("OEvortex/TTS-OLD", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| library_name: transformers | |
| tags: | |
| - text-to-speech | |
| - annotation | |
| license: apache-2.0 | |
| language: | |
| - en | |
| - as | |
| - bn | |
| - gu | |
| - hi | |
| - kn | |
| - ks | |
| - or | |
| - ml | |
| - mr | |
| - ne | |
| - pa | |
| - sa | |
| - sd | |
| - ta | |
| - te | |
| - ur | |
| - om | |
| pipeline_tag: text-to-speech | |
| inference: false | |
| base_model: | |
| - ai4bharat/indic-parler-tts | |
| # HelpingAI-TTS-v1 🎤🔥 | |
| Yo, what's good! Welcome to **HelpingAI-TTS-v1**, your go-to for next-level Text-to-Speech (TTS) that's all about personalization, vibes, and clarity. Whether you want your text to sound cheerful, emotional, or just like you're chatting with a friend, this model's got you covered. 💯 | |
| ## 🚀 What’s HelpingAI-TTS-v1? | |
| **HelpingAI-TTS-v1** is a beast when it comes to generating **high-quality, customizable speech**. It doesn’t just spit out generic text; it **feels** what you're saying and brings it to life with style. Add a description to your speech, like how fast or slow it should be, if it’s cheerful or serious, and BOOM — you got yourself the perfect audio output. 🎧 | |
| ## 🛠️ How It Works: A Quick Rundown 🔥 | |
| 1. **Transcript**: The text you want to speak. Keep it casual, formal, or whatever suits your vibe. | |
| 2. **Caption**: Describes how you want the speech to sound. Want a fast-paced, hype vibe or a calm, soothing tone? Just say it. 🔥 | |
| ## 💡 Features You’ll Love: | |
| - **Expressive Speech**: This isn’t just any TTS. You can describe the tone, speed, and vibe you want. Whether it's a *peppy* "Hey!" or a *chill* "What's up?", this model’s got your back. | |
| - **Top-Notch Quality**: Super clean audio. No static. Just pure, high-quality sound that makes your words pop. | |
| - **Customizable Like Never Before**: Play with emotions, tone, and even accents. It’s all about making it personal. 🌍 | |
| ## 🔧 Get Started: Installation 🔥 | |
| Ready to vibe? Here’s how you set up **HelpingAI-TTS-v1** in seconds: | |
| ```bash | |
| pip install git+https://github.com/huggingface/parler-tts.git | |
| ``` | |
| ## 🖥️ Usage: Let's Make Some Magic 🎤 | |
| Here’s the code that gets the job done. Super simple to use, just plug in your text and describe how you want it to sound. It’s like setting the mood for a movie. | |
| ```python | |
| import torch | |
| from parler_tts import ParlerTTSForConditionalGeneration | |
| from transformers import AutoTokenizer | |
| import soundfile as sf | |
| # Choose your device (GPU or CPU) | |
| device = "cuda:0" if torch.cuda.is_available() else "cpu" | |
| # Load the model and tokenizers | |
| model = ParlerTTSForConditionalGeneration.from_pretrained("HelpingAI/HelpingAI-TTS-v1").to(device) | |
| tokenizer = AutoTokenizer.from_pretrained("HelpingAI/HelpingAI-TTS-v1") | |
| description_tokenizer = AutoTokenizer.from_pretrained(model.config.text_encoder._name_or_path) | |
| # Customize your inputs: text + description | |
| prompt = "Hey, what's up? How’s it going?" | |
| description = "A friendly, upbeat, and casual tone with a moderate speed. Speaker sounds confident and relaxed." | |
| # Tokenize the inputs | |
| input_ids = description_tokenizer(description, return_tensors="pt").input_ids.to(device) | |
| prompt_input_ids = tokenizer(prompt, return_tensors="pt").input_ids.to(device) | |
| # Generate the audio | |
| generation = model.generate(input_ids=input_ids, prompt_input_ids=prompt_input_ids) | |
| audio_arr = generation.cpu().numpy().squeeze() | |
| # Save the audio to a file | |
| sf.write("output.wav", audio_arr, model.config.sampling_rate) | |
| ``` | |
| This will create a **super clean** `.wav` file with the speech you asked for. 🔥 | |
| ## 🌍 Language Support: Speak Your Language | |
| No matter where you're from, **HelpingAI-TTS-v1** has you covered. **Officially** supporting 20+ languages and **unofficial** support for a few more. That’s global vibes right there. 🌏 | |
| - Assamese | |
| - Bengali | |
| - Bodo | |
| - Dogri | |
| - Kannada | |
| - Malayalam | |
| - Marathi | |
| - Sanskrit | |
| - Nepali | |
| - English | |
| - Telugu | |
| - Hindi | |
| - Gujarati | |
| - Konkani | |
| - Maithili | |
| - Manipuri | |
| - Odia | |
| - Santali | |
| - Sindhi | |
| - Tamil | |
| - Urdu | |
| - Chhattisgarhi | |
| - Kashmiri | |
| - Punjabi | |
| *Powered by HelpingAI, where we blend emotional intelligence with tech.* 🌟 |