maya-research/Veena
text-to-speech model by maya-research
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From the publisher
Model card & documentation
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Veena is a state-of-the-art neural text-to-speech (TTS) model developed by Maya Research, designed for English and Indian languages. Built on a Llama architecture backbone, Veena generates natural, expressive speech with emotional tone, remarkable quality, and ultra-low latency. It represents the foundation of our voice intelligence work, bringing human-like voice to the two most spoken languages in the world. Veena is a 3B parameter autoregressive transformer model based on the Llama architecture. It is designed to synthesize high-quality speech from text in Hindi and English, including code-mixed scenarios. The model outputs audio at a 24kHz sampling rate using the SNAC neural codec. To use Veena, you need to install the transformers, torch, torchaudio, snac, and bitsandbytes libraries. The following Python code demonstrates how to generate speech from text using Veena with 4-bit quantization for efficient inference. Veena is ideal…
Read the full model card ↗ · Preview checked 2026-10-28T14:38:02.151Z
Inside the original model card — Document outline
- Veena - Text to Speech for Indian Languages
- Model Overview
- Key Features
- How to Get Started with the Model
- Installation
- Basic Usage
- Uses
- Technical Specifications
- Architecture
- Training
- Training Infrastructure
- Training Configuration
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Documentation belongs to its respective authors. Reported project/model license: apache-2.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
maya-research/Veena is a text-to-speech model repository published by maya-research on Hugging Face. The source reports the transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- text-to-speech
- Library
- transformers
- Recent downloads (30 days)
- 10,115
- Cumulative likes
- 240
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 3,783,054,336
- Architecture
- LlamaForCausalLM
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2025-06-24T23:58:58.000Z
- Last modified
- 2025-10-05T06:17:53.000Z
Compatibility and lineage
Reported languages: en, hi
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-09-22T06:37:21.297Z. Daily imports are snapshots, not real-time monitoring.
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