Instructions to use hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification") model = AutoModelForAudioClassification.from_pretrained("hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification: direct link, hf CLI and curl.
- Browser
- Download file 153 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification/resolve/refs%2Fpr%2F6/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification@refs/pr/6/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification/resolve/refs%2Fpr%2F6/pytorch_model.bin
153 kB
- Xet hash:
- b0750dcdb20972e0bd0b8ef56ebffbe62b0b1c2d0db3e4e9f16c2d3ea2f8d74d
- Size of remote file:
- 153 kB
- SHA256:
- 8bc743805e21b28e12bbf9238159475f8f0b6083cdd5da74e958645d94929ec3
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