Instructions to use lithish2602/sample_data with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lithish2602/sample_data with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="lithish2602/sample_data")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("lithish2602/sample_data") model = AutoModelForTextToSpectrogram.from_pretrained("lithish2602/sample_data", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from lithish2602/sample_data: direct link, hf CLI and curl.
- Browser
- Download file 578 MB
-
https://huggingface.co/lithish2602/sample_data/resolve/main/model.safetensors
- Command line
-
hf download hf://lithish2602/sample_data/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/lithish2602/sample_data/resolve/main/model.safetensors
578 MB
- Xet hash:
- b256cc37687fbe2a1a4b3b2edc5dca93720adc4a0aa2f1cd5e84491eff0e2f0f
- Size of remote file:
- 578 MB
- SHA256:
- 94ef92b7fd7d6d36eccfb499efb90f153a67c72297e378d7fd8ba06f4eab27bf
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