Instructions to use snorbyte/snorTTS-Indic-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use snorbyte/snorTTS-Indic-v0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="snorbyte/snorTTS-Indic-v0")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("snorbyte/snorTTS-Indic-v0") model = AutoModelForCausalLM.from_pretrained("snorbyte/snorTTS-Indic-v0") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use snorbyte/snorTTS-Indic-v0 with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for snorbyte/snorTTS-Indic-v0 to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for snorbyte/snorTTS-Indic-v0 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for snorbyte/snorTTS-Indic-v0 to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="snorbyte/snorTTS-Indic-v0", max_seq_length=2048, )
Finetune on custom voice using the snorbyte/snorTTS-Indic-v0
so I have single speaker High quality 30 hours of data, I have doubt can I fin tune your finetuned model on top of my voice dataset, as the script provided by u is from the base model of orpheus , I want to use your finetuned snorbyte/snorTTS-Indic-v0 model to further finetune on my custom voice. what parameters do I need to change, what should I do?
Hi, you have to format the dataset in SNAC encoding. Please refer to https://huggingface.co/datasets/snorbyte/indic-tts-sample-snac-encoded to see the format. Only utterance, user and language and SNAC codes are mandatory.
To finetune on your dataset just make the following changes. I have marked the changes below.
# Set up constants and configurations.
STAGE = 2 # <---------- changed
HUGGINGFACE_USERNAME = "" # ! Fill.
if STAGE == 1:
# No changes required ...
else:
BASE_MODEL = "snorbyte/snorTTS-Indic-v0" # <---------- changed
TARGET_MODULES = [
"q_proj",
"k_proj",
"v_proj",
"o_proj",
"up_proj",
"down_proj",
"gate_proj",
]
TRAIN_CSV_PATH = "" # ! Fill.
VALID_CSV_PATH = "" # ! Fill.
LR = 2e-4
EPOCHS = 2
MODEL_NAME = "snorTTS-indicv0-custom" # <---------- changed