Instructions to use microsoft/unispeech-sat-base-plus-sd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/unispeech-sat-base-plus-sd with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioFrameClassification processor = AutoProcessor.from_pretrained("microsoft/unispeech-sat-base-plus-sd") model = AutoModelForAudioFrameClassification.from_pretrained("microsoft/unispeech-sat-base-plus-sd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from microsoft/unispeech-sat-base-plus-sd: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/microsoft/unispeech-sat-base-plus-sd/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://microsoft/unispeech-sat-base-plus-sd/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/microsoft/unispeech-sat-base-plus-sd/resolve/main/pytorch_model.bin
378 MB
- Xet hash:
- c575f393a72fd65b73e873ad702d89e0123b8f1d94aa7f40e5e5d1b1345a3e66
- Size of remote file:
- 378 MB
- SHA256:
- fd69c3ce61ee7c06dc99ad997ce3c1296550b2a801a842baf8137210d9a19802
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.