Instructions to use yarik921/Teflon_0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yarik921/Teflon_0.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="yarik921/Teflon_0.1")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("yarik921/Teflon_0.1") model = AutoModelForCTC.from_pretrained("yarik921/Teflon_0.1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from yarik921/Teflon_0.1: direct link, hf CLI and curl.
- Browser
- Download file 388 Bytes
-
https://huggingface.co/yarik921/Teflon_0.1/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://yarik921/Teflon_0.1/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/yarik921/Teflon_0.1/resolve/main/tokenizer_config.json
388 Bytes
| {"unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>", "pad_token": "<pad>", "do_lower_case": true, "word_delimiter_token": "|", "special_tokens_map_file": "/scratch/work/getmany1/wav2vec/wav2vec2_large_100k_with_SWE_vocab_13_03_2021/special_tokens_map.json", "tokenizer_file": null, "name_or_path": "/scratch/work/getmany1/wav2vec/wav2vec2_large_100k_with_SWE_vocab_13_03_2021"} |