Instructions to use hadiqa123/XLS-R_timit_en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hadiqa123/XLS-R_timit_en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hadiqa123/XLS-R_timit_en")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("hadiqa123/XLS-R_timit_en") model = AutoModelForCTC.from_pretrained("hadiqa123/XLS-R_timit_en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from hadiqa123/XLS-R_timit_en: direct link, hf CLI and curl.
- Browser
- Download file 217 Bytes
-
https://huggingface.co/hadiqa123/XLS-R_timit_en/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://hadiqa123/XLS-R_timit_en/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/hadiqa123/XLS-R_timit_en/resolve/main/tokenizer_config.json
217 Bytes
| {"unk_token": "[UNK]", "bos_token": "<s>", "eos_token": "</s>", "pad_token": "[PAD]", "do_lower_case": false, "word_delimiter_token": "|", "replace_word_delimiter_char": " ", "tokenizer_class": "Wav2Vec2CTCTokenizer"} |