Instructions to use SHENMU007/neunit0424 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SHENMU007/neunit0424 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="SHENMU007/neunit0424")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("SHENMU007/neunit0424") model = AutoModelForTextToSpectrogram.from_pretrained("SHENMU007/neunit0424", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SHENMU007/neunit0424: direct link, hf CLI and curl.
- Browser
- Download file 586 MB
-
https://huggingface.co/SHENMU007/neunit0424/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SHENMU007/neunit0424/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SHENMU007/neunit0424/resolve/main/pytorch_model.bin
586 MB
- Xet hash:
- 4ea42f4583ccbd823ed25d5221ae917ac01e76ff29b78611ac66f6c390484ca2
- Size of remote file:
- 586 MB
- SHA256:
- 0aa4749c7eb50483a4067f6e062ab8c382a35c49f15f0abc5afb050166be55a2
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