Instructions to use hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification") model = AutoModelForAudioClassification.from_pretrained("hf-internal-testing/tiny-random-Wav2Vec2ForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
| { | |
| "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>", | |
| "replace_word_delimiter_char": " ", | |
| "return_attention_mask": false, | |
| "tokenizer_class": "Wav2Vec2CTCTokenizer", | |
| "unk_token": "<unk>", | |
| "word_delimiter_token": "|" | |
| } | |