Instructions to use hf-internal-testing/tiny-random-WavLMForAudioFrameClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-WavLMForAudioFrameClassification with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioFrameClassification processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-WavLMForAudioFrameClassification") model = AutoModelForAudioFrameClassification.from_pretrained("hf-internal-testing/tiny-random-WavLMForAudioFrameClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-internal-testing/tiny-random-WavLMForAudioFrameClassification: direct link, hf CLI and curl.
- Browser
- Download file 141 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-WavLMForAudioFrameClassification/resolve/d4c06a92c537627bc1a400d7b565d97d05440623/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-WavLMForAudioFrameClassification@d4c06a92c537627bc1a400d7b565d97d05440623/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-WavLMForAudioFrameClassification/resolve/d4c06a92c537627bc1a400d7b565d97d05440623/pytorch_model.bin
141 kB
- Xet hash:
- e8bbdb65ed82586341cd3e5df932785e97344059c6594a85ff6e3e39c23c022d
- Size of remote file:
- 141 kB
- SHA256:
- 2cbf4191811d5d68f0398257b4386e7d141c9ebf181559f93edb7ff9131ac8a1
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