Instructions to use lsnoo/temporal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lsnoo/temporal with Transformers:
# Load model directly from transformers import AutoProcessor, Wav2Vec2ForSpeechClassification processor = AutoProcessor.from_pretrained("lsnoo/temporal") model = Wav2Vec2ForSpeechClassification.from_pretrained("lsnoo/temporal", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from lsnoo/temporal: direct link, hf CLI and curl.
- Browser
- Download file 279 Bytes
-
https://huggingface.co/lsnoo/temporal/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://lsnoo/temporal/preprocessor_config.json
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curl -L -o preprocessor_config.json https://huggingface.co/lsnoo/temporal/resolve/main/preprocessor_config.json
279 Bytes
| { | |
| "cache_dir": "/data2/excalibur12/.cache/huggingface/datasets", | |
| "do_normalize": true, | |
| "feature_extractor_type": "Wav2Vec2FeatureExtractor", | |
| "feature_size": 1, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "return_attention_mask": true, | |
| "sampling_rate": 16000 | |
| } | |