Instructions to use hf-internal-testing/tiny-random-Data2VecAudioForAudioFrameClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Data2VecAudioForAudioFrameClassification with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForAudioFrameClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-Data2VecAudioForAudioFrameClassification") model = AutoModelForAudioFrameClassification.from_pretrained("hf-internal-testing/tiny-random-Data2VecAudioForAudioFrameClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
hf-transformers-bot HF Staff
Upload tiny models for Data2VecAudioForAudioFrameClassification
a64828b Download preprocessor_config.json from hf-internal-testing/tiny-random-Data2VecAudioForAudioFrameClassification: direct link, hf CLI and curl.
- Browser
- Download file 256 Bytes
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https://huggingface.co/hf-internal-testing/tiny-random-Data2VecAudioForAudioFrameClassification/resolve/28ab3fa763436a742b038a0f1ab3832450412a33/preprocessor_config.json
- Command line
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hf download hf://hf-internal-testing/tiny-random-Data2VecAudioForAudioFrameClassification@28ab3fa763436a742b038a0f1ab3832450412a33/preprocessor_config.json
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curl -L -o preprocessor_config.json https://huggingface.co/hf-internal-testing/tiny-random-Data2VecAudioForAudioFrameClassification/resolve/28ab3fa763436a742b038a0f1ab3832450412a33/preprocessor_config.json
256 Bytes
| { | |
| "do_normalize": true, | |
| "feature_extractor_type": "Wav2Vec2FeatureExtractor", | |
| "feature_size": 1, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "processor_class": "Wav2Vec2Processor", | |
| "return_attention_mask": true, | |
| "sampling_rate": 16000 | |
| } | |