Instructions to use omarimc/dst with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use omarimc/dst with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="omarimc/dst")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToWaveform processor = AutoProcessor.from_pretrained("omarimc/dst") model = AutoModelForTextToWaveform.from_pretrained("omarimc/dst", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download compression_state_dict.bin from omarimc/dst: direct link, hf CLI and curl.
- Browser
- Download file 236 MB
-
https://huggingface.co/omarimc/dst/resolve/main/compression_state_dict.bin
- Command line
-
hf download hf://omarimc/dst/compression_state_dict.bin
-
curl -L -o compression_state_dict.bin https://huggingface.co/omarimc/dst/resolve/main/compression_state_dict.bin
236 MB
- Xet hash:
- aaacdb35624dd83e67ba3ed22af84276f934279d52d9dc3dea662d23fd69e798
- Size of remote file:
- 236 MB
- SHA256:
- 37d256b525d4117f8bbf790ab448a8e9f4746cd401900fe1ae72e154b1513a30
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