Instructions to use SHENMU007/neunit_testv1.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SHENMU007/neunit_testv1.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="SHENMU007/neunit_testv1.1")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("SHENMU007/neunit_testv1.1") model = AutoModelForTextToSpectrogram.from_pretrained("SHENMU007/neunit_testv1.1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SHENMU007/neunit_testv1.1: direct link, hf CLI and curl.
- Browser
- Download file 585 MB
-
https://huggingface.co/SHENMU007/neunit_testv1.1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SHENMU007/neunit_testv1.1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SHENMU007/neunit_testv1.1/resolve/main/pytorch_model.bin
585 MB
- Xet hash:
- 752fbccd179054c146b1723a4ca8da1522de20271ca1bf3c41ae624c6dbe1381
- Size of remote file:
- 585 MB
- SHA256:
- a4a4a9dbfae2f69e5c578eac9fbeb576cb9abbbad8d90e6477ce1ede70d2f12d
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