Instructions to use monideep2255/batch_size_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use monideep2255/batch_size_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="monideep2255/batch_size_2")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("monideep2255/batch_size_2") model = AutoModelForCTC.from_pretrained("monideep2255/batch_size_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 484 Bytes
46f17b6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | {
"bos_token": "<s>",
"clean_up_tokenization_spaces": true,
"do_lower_case": false,
"eos_token": "</s>",
"model_max_length": 1000000000000000019884624838656,
"pad_token": "<pad>",
"replace_word_delimiter_char": " ",
"reserved_token1": "?reserved2?",
"reserved_token2": "?reserved3?",
"silence_token": "<sil>",
"spoken_noise_token": "<spn>",
"tokenizer_class": "Wav2Vec2CTCTokenizer",
"unk_token": "<unk>",
"vocab_size": 46,
"word_delimiter_token": "|"
}
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