Text-to-Speech
Transformers
Safetensors
llama
text-generation
tts
unsloth
audio
speech-synthesis
text-generation-inference
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 Settings
- Unsloth Studio
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, )
Error in stage 2 training of pipeline
#5
by Sainath0111 - opened
ERROR | main:generate_audio:119 - Error decoding audio: index out of range in self
2644 3562 1301 1513 7545 -19763 -16918 if inspect deeply SNAC tokens are crossing the limits
Can you please help how did you handle this in stage 2 of training.
That is one of the cons of these kinds of models: they can hallucinate and generate incorrect tokens. Maybe just try ignoring them.
You can also try guided decoding.
Fyi you should not see this error in training.
SaudxInu changed discussion status to closed