Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use jucielflexge/teste_finetunning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jucielflexge/teste_finetunning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jucielflexge/teste_finetunning")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("jucielflexge/teste_finetunning") model = AutoModelForCTC.from_pretrained("jucielflexge/teste_finetunning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d36c49cf0878caabf65bb668ae481e8d572a95435eb4b00ddddc7c87bf999afb
- Size of remote file:
- 5.18 kB
- SHA256:
- 35f6025ec0af327ad20fe99e44fd1e786b4683bcb8557db3aba82cdc57c9e450
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