Instructions to use SHENMU007/neunit0425_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SHENMU007/neunit0425_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="SHENMU007/neunit0425_base")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("SHENMU007/neunit0425_base") model = AutoModelForTextToSpectrogram.from_pretrained("SHENMU007/neunit0425_base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SHENMU007/neunit0425_base: direct link, hf CLI and curl.
- Browser
- Download file 585 MB
-
https://huggingface.co/SHENMU007/neunit0425_base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SHENMU007/neunit0425_base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SHENMU007/neunit0425_base/resolve/main/pytorch_model.bin
585 MB
- Xet hash:
- d192a81ca98a173d610b41cf08aaee0d9c4e432fb6e3ee381281c011940777bb
- Size of remote file:
- 585 MB
- SHA256:
- 9a886ff30b3e495a91833dacb789b2a542deea08220f9ce77e83e46be05bfde2
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