Audio Classification
Transformers
PyTorch
English
wav2vec2
pretraining
non-verbal-vocalization
baby-crying
Instructions to use alkiskoudounas/voc2vec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alkiskoudounas/voc2vec with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="alkiskoudounas/voc2vec")# Load model directly from transformers import AutoProcessor, AutoModelForPreTraining processor = AutoProcessor.from_pretrained("alkiskoudounas/voc2vec") model = AutoModelForPreTraining.from_pretrained("alkiskoudounas/voc2vec", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 419 Bytes
c9d8046 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"bos_token": "<s>",
"clean_up_tokenization_spaces": true,
"do_lower_case": false,
"do_normalize": true,
"eos_token": "</s>",
"model_max_length": 9223372036854775807,
"pad_token": "<pad>",
"processor_class": "Wav2Vec2Processor",
"replace_word_delimiter_char": " ",
"return_attention_mask": false,
"tokenizer_class": "Wav2Vec2CTCTokenizer",
"unk_token": "<unk>",
"word_delimiter_token": "|"
}
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