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%2F4/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification@refs/pr/4/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification/resolve/refs%2Fpr%2F4/pytorch_model.bin
153 kB
- Xet hash:
- 18b7278c7d166b410ff2e01f54fa762a3ae2ae217fbaebf37a8845b3e90e1dc2
- Size of remote file:
- 153 kB
- SHA256:
- ed4a184d0fd629b7725480ed9aa6a4acc69658d604e2fd18bbe4ebf2ae46b1ef
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