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/ab9d80b1e18f3128a16e861fbd3b681308148e9b/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-WavLMForAudioFrameClassification@ab9d80b1e18f3128a16e861fbd3b681308148e9b/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-WavLMForAudioFrameClassification/resolve/ab9d80b1e18f3128a16e861fbd3b681308148e9b/pytorch_model.bin
141 kB
- Xet hash:
- bc016197cc8445e566d6680f098f21e44ae08fb100b06aeaee84e2d40762436b
- Size of remote file:
- 141 kB
- SHA256:
- 4f3ae0a4c83bf6807a8682fa1b5b4b5cb4cdc4e83ff6f9627f3f71b54e7da3c1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.