Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Portuguese
wav2vec2
Generated from Trainer
hf-asr-leaderboard
mozilla-foundation/common_voice_7_0
robust-speech-event
Eval Results (legacy)
Instructions to use lgris/wav2vec2-xls-r-pt-cv7-from-bp400h with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lgris/wav2vec2-xls-r-pt-cv7-from-bp400h with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="lgris/wav2vec2-xls-r-pt-cv7-from-bp400h")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("lgris/wav2vec2-xls-r-pt-cv7-from-bp400h") model = AutoModelForCTC.from_pretrained("lgris/wav2vec2-xls-r-pt-cv7-from-bp400h", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| {"unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>", "pad_token": "<pad>", "do_lower_case": false, "word_delimiter_token": "|", "special_tokens_map_file": "/root/.cache/huggingface/transformers/a803f23f1afc428695542b16e67d92127ae59529b524e83b04b46e96c24e1dd5.9d6cd81ef646692fb1c169a880161ea1cb95f49694f220aced9b704b457e51dd", "tokenizer_file": null, "name_or_path": "lgris/wav2vec2-xls-r-pt-cv7-from-bp400h", "tokenizer_class": "Wav2Vec2CTCTokenizer", "processor_class": "Wav2Vec2ProcessorWithLM"} |