Automatic Speech Recognition
Transformers
PyTorch
JAX
Portuguese
wav2vec2
audio
speech
apache-2.0
portuguese-speech-corpus
xlsr-fine-tuning-week
PyTorch
Eval Results (legacy)
Instructions to use joaoalvarenga/model-sid-voxforge-cv-cetuc-0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use joaoalvarenga/model-sid-voxforge-cv-cetuc-0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="joaoalvarenga/model-sid-voxforge-cv-cetuc-0")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("joaoalvarenga/model-sid-voxforge-cv-cetuc-0") model = AutoModelForCTC.from_pretrained("joaoalvarenga/model-sid-voxforge-cv-cetuc-0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from joaoalvarenga/model-sid-voxforge-cv-cetuc-0: direct link, hf CLI and curl.
- Browser
- Download file 327 Bytes
-
https://huggingface.co/joaoalvarenga/model-sid-voxforge-cv-cetuc-0/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://joaoalvarenga/model-sid-voxforge-cv-cetuc-0/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/joaoalvarenga/model-sid-voxforge-cv-cetuc-0/resolve/main/tokenizer_config.json
327 Bytes
| {"unk_token": "[UNK]", "bos_token": "<s>", "eos_token": "</s>", "pad_token": "[PAD]", "do_lower_case": false, "word_delimiter_token": "|", "special_tokens_map_file": "/data/models/wav2vec2-sid-voxforge-cv-cetuc-0/special_tokens_map.json", "tokenizer_file": null, "name_or_path": "/data/models/wav2vec2-sid-voxforge-cv-cetuc-0"} |