Instructions to use arbml/wav2vec2-large-xlsr-dialect-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arbml/wav2vec2-large-xlsr-dialect-classification with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("arbml/wav2vec2-large-xlsr-dialect-classification") model = AutoModel.from_pretrained("arbml/wav2vec2-large-xlsr-dialect-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from arbml/wav2vec2-large-xlsr-dialect-classification: direct link, hf CLI and curl.
- Browser
- Download file 158 Bytes
-
https://huggingface.co/arbml/wav2vec2-large-xlsr-dialect-classification/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://arbml/wav2vec2-large-xlsr-dialect-classification/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/arbml/wav2vec2-large-xlsr-dialect-classification/resolve/main/preprocessor_config.json
158 Bytes
| { | |
| "do_normalize": true, | |
| "feature_size": 1, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "return_attention_mask": true, | |
| "sampling_rate": 16000 | |
| } | |