Instructions to use hf-internal-testing/tiny-random-ASTForAudioClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ASTForAudioClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="hf-internal-testing/tiny-random-ASTForAudioClassification")# pip install -U transformers accelerate # Load model directly from transformers import AutoFeatureExtractor, AutoModelForAudioClassification extractor = AutoFeatureExtractor.from_pretrained("hf-internal-testing/tiny-random-ASTForAudioClassification") model = AutoModelForAudioClassification.from_pretrained("hf-internal-testing/tiny-random-ASTForAudioClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-internal-testing/tiny-random-ASTForAudioClassification: direct link, hf CLI and curl.
- Browser
- Download file 181 kB
-
https://huggingface.co/hf-internal-testing/tiny-random-ASTForAudioClassification/resolve/83d6e076db7768a3645401bad3204624985e1d08/pytorch_model.bin
- Command line
-
hf download hf://hf-internal-testing/tiny-random-ASTForAudioClassification@83d6e076db7768a3645401bad3204624985e1d08/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-internal-testing/tiny-random-ASTForAudioClassification/resolve/83d6e076db7768a3645401bad3204624985e1d08/pytorch_model.bin
181 kB
- Xet hash:
- 9642dae173b07f5f3cbe25ad9ffc58c36ca7d19dbb1a77c193a32d590ee12e4e
- Size of remote file:
- 181 kB
- SHA256:
- ef6649323383fb261d94b601bbaf5ef2fea3a5d396ffc160c3410d51805dfa2f
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