metadata
base_model: snorbyte/snorTTS-Indic-v0
tags:
- text-to-speech
- tts
- transformers
- unsloth
- llama
- audio
- speech-synthesis
- TensorBlock
- GGUF
license: apache-2.0
language:
- hi
- gu
- mr
- pa
- bn
- te
- kn
- ml
- ta
snorbyte/snorTTS-Indic-v0 - GGUF
This repo contains GGUF format model files for snorbyte/snorTTS-Indic-v0.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b5753.
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Prompt template
<|begin_of_text|><|start_header_id|>system<|end_header_id|>
Cutting Knowledge Date: December 2023
Today Date: 07 Aug 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 |
|---|---|---|---|
| snorTTS-Indic-v0-Q2_K.gguf | Q2_K | 1.595 GB | smallest, significant quality loss - not recommended for most purposes |
| snorTTS-Indic-v0-Q3_K_S.gguf | Q3_K_S | 1.823 GB | very small, high quality loss |
| snorTTS-Indic-v0-Q3_K_M.gguf | Q3_K_M | 1.968 GB | very small, high quality loss |
| snorTTS-Indic-v0-Q3_K_L.gguf | Q3_K_L | 2.096 GB | small, substantial quality loss |
| snorTTS-Indic-v0-Q4_0.gguf | Q4_0 | 2.262 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| snorTTS-Indic-v0-Q4_K_S.gguf | Q4_K_S | 2.273 GB | small, greater quality loss |
| snorTTS-Indic-v0-Q4_K_M.gguf | Q4_K_M | 2.364 GB | medium, balanced quality - recommended |
| snorTTS-Indic-v0-Q5_0.gguf | Q5_0 | 2.674 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| snorTTS-Indic-v0-Q5_K_S.gguf | Q5_K_S | 2.674 GB | large, low quality loss - recommended |
| snorTTS-Indic-v0-Q5_K_M.gguf | Q5_K_M | 2.727 GB | large, very low quality loss - recommended |
| snorTTS-Indic-v0-Q6_K.gguf | Q6_K | 3.113 GB | very large, extremely low quality loss |
| snorTTS-Indic-v0-Q8_0.gguf | Q8_0 | 4.029 GB | very large, extremely low quality loss - not recommended |
Downloading instruction
Command line
Firstly, install Huggingface Client
pip install -U "huggingface_hub[cli]"
Then, downoad the individual model file the a local directory
huggingface-cli download tensorblock/snorbyte_snorTTS-Indic-v0-GGUF --include "snorTTS-Indic-v0-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:
huggingface-cli download tensorblock/snorbyte_snorTTS-Indic-v0-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'