Instructions to use lilitket/aspram with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lilitket/aspram with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="lilitket/aspram")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("lilitket/aspram") model = AutoModelForCTC.from_pretrained("lilitket/aspram", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from lilitket/aspram: direct link, hf CLI and curl.
- Browser
- Download file 338 Bytes
-
https://huggingface.co/lilitket/aspram/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://lilitket/aspram/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/lilitket/aspram/resolve/main/tokenizer_config.json
338 Bytes
| {"unk_token": "[UNK]", "bos_token": "<s>", "eos_token": "</s>", "pad_token": "[PAD]", "do_lower_case": false, "word_delimiter_token": "|", "replace_word_delimiter_char": " ", "special_tokens_map_file": null, "name_or_path": "20220428-094209--72000", "tokenizer_class": "Wav2Vec2CTCTokenizer", "processor_class": "Wav2Vec2ProcessorWithLM"} |