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%2F1/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification/resolve/refs%2Fpr%2F1/pytorch_model.bin
153 kB
- Xet hash:
- d5706f9ed73bfaa8e2c58cd59a2450639877ed385e88d4f402f114025b63d423
- Size of remote file:
- 153 kB
- SHA256:
- 626cc31c9d20a2a3c8a7d16fcf756fcbc4eddc99243c53268e45a1ab439d2634
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