Automatic Speech Recognition
Transformers
PyTorch
Safetensors
Czech
wav2vec2
Generated from Trainer
hf-asr-leaderboard
mozilla-foundation/common_voice_8_0
robust-speech-event
xlsr-fine-tuning-week
Eval Results (legacy)
Instructions to use comodoro/wav2vec2-xls-r-300m-cs-250 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use comodoro/wav2vec2-xls-r-300m-cs-250 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="comodoro/wav2vec2-xls-r-300m-cs-250")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("comodoro/wav2vec2-xls-r-300m-cs-250") model = AutoModelForCTC.from_pretrained("comodoro/wav2vec2-xls-r-300m-cs-250") - Notebooks
- Google Colab
- Kaggle
File size: 300 Bytes
a4b44de | 1 | {"unk_token": "[UNK]", "bos_token": "<s>", "eos_token": "</s>", "pad_token": "[PAD]", "do_lower_case": false, "word_delimiter_token": "|", "special_tokens_map_file": null, "tokenizer_file": null, "name_or_path": "./", "tokenizer_class": "Wav2Vec2CTCTokenizer", "processor_class": "Wav2Vec2Processor"} |