Instructions to use hf-tiny-model-private/tiny-random-UniSpeechModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-UniSpeechModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-tiny-model-private/tiny-random-UniSpeechModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-UniSpeechModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-UniSpeechModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-tiny-model-private/tiny-random-UniSpeechModel: direct link, hf CLI and curl.
- Browser
- Download file 132 kB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-UniSpeechModel/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-UniSpeechModel/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-tiny-model-private/tiny-random-UniSpeechModel/resolve/main/pytorch_model.bin
132 kB
- Xet hash:
- 17436718fc98d080e0447516beb60ddd54bb39e42276c5f95a3e6c13a8c05177
- Size of remote file:
- 132 kB
- SHA256:
- 01e20d257d137ac32be97d0af3767f3a8d7b307e6cd35962bc7a7ac87ffae38b
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