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 special_tokens_map.json from joaoalvarenga/model-sid-voxforge-cv-cetuc-0: direct link, hf CLI and curl.
- Browser
- Download file 85 Bytes
-
https://huggingface.co/joaoalvarenga/model-sid-voxforge-cv-cetuc-0/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://joaoalvarenga/model-sid-voxforge-cv-cetuc-0/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/joaoalvarenga/model-sid-voxforge-cv-cetuc-0/resolve/main/special_tokens_map.json
85 Bytes
| {"bos_token": "<s>", "eos_token": "</s>", "unk_token": "[UNK]", "pad_token": "[PAD]"} |