Instructions to use SHENMU007/neunit_tts_BASE_V1.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SHENMU007/neunit_tts_BASE_V1.2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="SHENMU007/neunit_tts_BASE_V1.2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForTextToSpectrogram processor = AutoProcessor.from_pretrained("SHENMU007/neunit_tts_BASE_V1.2") model = AutoModelForTextToSpectrogram.from_pretrained("SHENMU007/neunit_tts_BASE_V1.2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SHENMU007/neunit_tts_BASE_V1.2: direct link, hf CLI and curl.
- Browser
- Download file 585 MB
-
https://huggingface.co/SHENMU007/neunit_tts_BASE_V1.2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SHENMU007/neunit_tts_BASE_V1.2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SHENMU007/neunit_tts_BASE_V1.2/resolve/main/pytorch_model.bin
585 MB
- Xet hash:
- ca759eebaa3473b89b091abae8630d393dd6960d185f49ffc08f21710ac57097
- Size of remote file:
- 585 MB
- SHA256:
- b4b31c3e03d70c1569331902a11ecc5af2591a24d933cda61b3ce6f662bdc28e
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