Instructions to use SHENMU007/neunit0425 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SHENMU007/neunit0425 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="SHENMU007/neunit0425")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("SHENMU007/neunit0425") model = AutoModelForTextToSpectrogram.from_pretrained("SHENMU007/neunit0425", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SHENMU007/neunit0425: direct link, hf CLI and curl.
- Browser
- Download file 586 MB
-
https://huggingface.co/SHENMU007/neunit0425/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SHENMU007/neunit0425/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SHENMU007/neunit0425/resolve/main/pytorch_model.bin
586 MB
- Xet hash:
- ccc4f27f028f95171a76e9e545423b6c2c44f8fd0638fc5ce19e59d667db22c2
- Size of remote file:
- 586 MB
- SHA256:
- d285ea43a49f5d5e38fec1e9147146a1086f7224db9911ed012dced06c65fdea
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