Instructions to use MathRaaj/wav2vec-bert-ser-standard with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MathRaaj/wav2vec-bert-ser-standard with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import W2VBertSER model = W2VBertSER.from_pretrained("MathRaaj/wav2vec-bert-ser-standard", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from MathRaaj/wav2vec-bert-ser-standard: direct link, hf CLI and curl.
- Browser
- Download file 229 Bytes
-
https://huggingface.co/MathRaaj/wav2vec-bert-ser-standard/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://MathRaaj/wav2vec-bert-ser-standard/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/MathRaaj/wav2vec-bert-ser-standard/resolve/main/preprocessor_config.json
229 Bytes
| { | |
| "feature_extractor_type": "SeamlessM4TFeatureExtractor", | |
| "feature_size": 80, | |
| "num_mel_bins": 80, | |
| "padding_side": "right", | |
| "padding_value": 1, | |
| "return_attention_mask": true, | |
| "sampling_rate": 16000, | |
| "stride": 2 | |
| } | |