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/a849f077bb6bc12491f3aeb9601cc89ca3f56b2c/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification@a849f077bb6bc12491f3aeb9601cc89ca3f56b2c/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification/resolve/a849f077bb6bc12491f3aeb9601cc89ca3f56b2c/pytorch_model.bin
153 kB
- Xet hash:
- d3aba8181d982189a312de591a488469b1240df1c1c39c6b7da7643617a9569b
- Size of remote file:
- 153 kB
- SHA256:
- f8e295d1a4a10765558b89b77d6d4883f7e5c2357dd96c1e8a827b3fd44e6d41
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