Instructions to use Renderlib-dev/sooktam2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Renderlib-dev/sooktam2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="Renderlib-dev/sooktam2", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Renderlib-dev/sooktam2", trust_remote_code=True, dtype="auto") - F5-TTS
How to use Renderlib-dev/sooktam2 with F5-TTS:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
File size: 965 Bytes
bccbc5b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | #!/bin/bash
set -e
# apt update
# apt-get install libavformat-dev libavdevice-dev -y
# if gpu is available
if [ -n "$(lspci | grep NVIDIA)" ]; then
apt-get install libcudnn9-cuda-12 -y
fi
pip install torch==2.6.0 torchaudio==2.6.0 torchvision==0.21.0 transformers==4.41.2 huggingface-hub==0.24.7 indic-nlp-library==0.92
echo "Installing dependencies for prepare_cls_version.py..."
pip install \
datasets==4.5.0 \
tqdm \
indo-arabic-transliteration==0.1.5 \
indic-unified-parser==1.0.6 \
indic-numtowords==1.1.0 \
indic-nlp-library==0.92 \
git+https://github.com/libindic/indic-trans.git@0287fa62289968f0ce06cbe2df61cfadf4088c75 \
urduhack==1.1.1 \
keras==2.15.0 \
tensorflow==2.15.0 \
tensorflow-addons==0.23.0 \
fastapi==0.128.7 \
uvicorn==0.40.0
pip install indic_unified_parser==1.0.6 indo-arabic-transliteration==0.1.5 indic-numtowords==1.1.0
pip install click==8.0.1
pip install -e . --no-cache-dir
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