Instructions to use bezzam/parakeet-ctc-1.1b-hf-sequential with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bezzam/parakeet-ctc-1.1b-hf-sequential with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="bezzam/parakeet-ctc-1.1b-hf-sequential")# Load model directly from transformers import AutoModelForCTC model = AutoModelForCTC.from_pretrained("bezzam/parakeet-ctc-1.1b-hf-sequential", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "added_tokens_decoder": { | |
| "0": { | |
| "content": "<unk>", | |
| "lstrip": false, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false, | |
| "special": true | |
| } | |
| }, | |
| "blank_token_id": 1024, | |
| "clean_up_tokenization_spaces": false, | |
| "do_lower_case": false, | |
| "extra_special_tokens": {}, | |
| "model_max_length": 1000000000000000019884624838656, | |
| "processor_class": "ParakeetProcessor", | |
| "tokenizer_class": "ParakeetCTCTokenizer", | |
| "unk_token": "<unk>" | |
| } | |