Instructions to use Vijish/mms with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Vijish/mms with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="Vijish/mms")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForPreTraining tokenizer = AutoTokenizer.from_pretrained("Vijish/mms") model = AutoModelForPreTraining.from_pretrained("Vijish/mms", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Vijish/mms: direct link, hf CLI and curl.
- Browser
- Download file 145 MB
-
https://huggingface.co/Vijish/mms/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Vijish/mms/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Vijish/mms/resolve/main/pytorch_model.bin
145 MB
- Xet hash:
- 29b8bd757eb125bcd9c6ae940a11d0c1e5578f4616069e96108d166450700e28
- Size of remote file:
- 145 MB
- SHA256:
- c1dadef52164d5c604ecfd5c9a3370c37d363972537e9881869ff393c3d62aba
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