---
license: apache-2.0
language:
- en
- hi
library_name: transformers
tags:
- text-to-speech
- tts
- hindi
- english
- llama
- audio
- speech
- india
- TensorBlock
- GGUF
datasets:
- proprietary
pipeline_tag: text-to-speech
co2_eq_emissions:
  emissions: 0
  source: Not specified
  training_type: unknown
  geographical_location: unknown
base_model: maya-research/Veena
---

<div style="width: auto; margin-left: auto; margin-right: auto">
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## maya-research/Veena - GGUF

<div style="text-align: left; margin: 20px 0;">
    <a href="https://discord.com/invite/Ej5NmeHFf2" style="display: inline-block; padding: 10px 20px; background-color: #5865F2; color: white; text-decoration: none; border-radius: 5px; font-weight: bold;">
        Join our Discord to learn more about what we're building ↗
    </a>
</div>

This repo contains GGUF format model files for [maya-research/Veena](https://huggingface.co/maya-research/Veena).

The files were quantized using machines provided by [TensorBlock](https://tensorblock.co/), and they are compatible with llama.cpp as of [commit b5753](https://github.com/ggml-org/llama.cpp/commit/73e53dc834c0a2336cd104473af6897197b96277).

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      ">👀 See what we built 👀</a>
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</table>

## Prompt template

```
<|begin_of_text|><|start_header_id|>system<|end_header_id|>

Cutting Knowledge Date: December 2023
Today Date: 21 Jul 2025

{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>

{prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
```

## Model file specification

| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [Veena-Q2_K.gguf](https://huggingface.co/tensorblock/maya-research_Veena-GGUF/blob/main/Veena-Q2_K.gguf) | Q2_K | 1.595 GB | smallest, significant quality loss - not recommended for most purposes |
| [Veena-Q3_K_S.gguf](https://huggingface.co/tensorblock/maya-research_Veena-GGUF/blob/main/Veena-Q3_K_S.gguf) | Q3_K_S | 1.823 GB | very small, high quality loss |
| [Veena-Q3_K_M.gguf](https://huggingface.co/tensorblock/maya-research_Veena-GGUF/blob/main/Veena-Q3_K_M.gguf) | Q3_K_M | 1.968 GB | very small, high quality loss |
| [Veena-Q3_K_L.gguf](https://huggingface.co/tensorblock/maya-research_Veena-GGUF/blob/main/Veena-Q3_K_L.gguf) | Q3_K_L | 2.096 GB | small, substantial quality loss |
| [Veena-Q4_0.gguf](https://huggingface.co/tensorblock/maya-research_Veena-GGUF/blob/main/Veena-Q4_0.gguf) | Q4_0 | 2.262 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| [Veena-Q4_K_S.gguf](https://huggingface.co/tensorblock/maya-research_Veena-GGUF/blob/main/Veena-Q4_K_S.gguf) | Q4_K_S | 2.273 GB | small, greater quality loss |
| [Veena-Q4_K_M.gguf](https://huggingface.co/tensorblock/maya-research_Veena-GGUF/blob/main/Veena-Q4_K_M.gguf) | Q4_K_M | 2.364 GB | medium, balanced quality - recommended |
| [Veena-Q5_0.gguf](https://huggingface.co/tensorblock/maya-research_Veena-GGUF/blob/main/Veena-Q5_0.gguf) | Q5_0 | 2.674 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| [Veena-Q5_K_S.gguf](https://huggingface.co/tensorblock/maya-research_Veena-GGUF/blob/main/Veena-Q5_K_S.gguf) | Q5_K_S | 2.674 GB | large, low quality loss - recommended |
| [Veena-Q5_K_M.gguf](https://huggingface.co/tensorblock/maya-research_Veena-GGUF/blob/main/Veena-Q5_K_M.gguf) | Q5_K_M | 2.727 GB | large, very low quality loss - recommended |
| [Veena-Q6_K.gguf](https://huggingface.co/tensorblock/maya-research_Veena-GGUF/blob/main/Veena-Q6_K.gguf) | Q6_K | 3.113 GB | very large, extremely low quality loss |
| [Veena-Q8_0.gguf](https://huggingface.co/tensorblock/maya-research_Veena-GGUF/blob/main/Veena-Q8_0.gguf) | Q8_0 | 4.029 GB | very large, extremely low quality loss - not recommended |


## Downloading instruction

### Command line

Firstly, install Huggingface Client

```shell
pip install -U "huggingface_hub[cli]"
```

Then, downoad the individual model file the a local directory

```shell
huggingface-cli download tensorblock/maya-research_Veena-GGUF --include "Veena-Q2_K.gguf" --local-dir MY_LOCAL_DIR
```

If you wanna download multiple model files with a pattern (e.g., `*Q4_K*gguf`), you can try:

```shell
huggingface-cli download tensorblock/maya-research_Veena-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
```