README.md

---
license: cc-by-4.0
datasets:
- speechcolab/gigaspeech
- parler-tts/mls_eng_10k
- reach-vb/jenny_tts_dataset
language:
- en
- hi
base_model:
- openai-community/gpt2
pipeline_tag: text-to-speech
---

# Model Card for Model ID

Indri is a series of audio models that can do TTS, ASR, and audio continuation. This is the smallest model in our series and supports TTS tasks in 2 languages:
1. English
2. Hindi


## Model Details

### Model Description

`indri-0.1-125m-tts` is a novel, extremely small, and lightweight TTS model based on the transformer architecture.
It models audio as tokens and can generate high-quality audio with consistent style cloning of the speaker.

### Key features

1. Based on GPT-2 architecture
2. Supports voice cloning with small prompts
3. Code mixing text input in 2 languages - English and Hindi

### Model Sources [optional]

- **Repository:** [https://github.com/cmeraki/indri]
- **Demo:** [https://www.indrivoice.ai/]

## Technical details

Please read our blog [here]() for more technical details on how it was built.

Here's a brief of how this model works:

1. Converts input text into tokens
2. Runs autoregressive decoding on GPT-2 based transformer model and generates audio tokens
3. Decodes audio tokens (from [Kyutaui/mimi](https://huggingface.co/kyutai/mimi)) to audio

## How to Get Started with the Model

Use the code below to get started with the model.

## Training Details

### Training Data

<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->

[More Information Needed]

### Training Procedure

<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->

#### Preprocessing [optional]

[More Information Needed]


#### Training Hyperparameters

- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->

#### Speeds, Sizes, Times [optional]

<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->

[More Information Needed]

## Citation [optional]

<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->

**BibTeX:**

[More Information Needed]