Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
speech-encoder-decoder
librispeech_asr
Generated from Trainer
asr_seq2esq
Instructions to use patrickvonplaten/wav2vec2-2-bart-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use patrickvonplaten/wav2vec2-2-bart-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="patrickvonplaten/wav2vec2-2-bart-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSpeechSeq2Seq tokenizer = AutoTokenizer.from_pretrained("patrickvonplaten/wav2vec2-2-bart-base") model = AutoModelForSpeechSeq2Seq.from_pretrained("patrickvonplaten/wav2vec2-2-bart-base") - Notebooks
- Google Colab
- Kaggle
| timestamp,experiment_id,project_name,duration,emissions,energy_consumed,country_name,country_iso_code,region,on_cloud,cloud_provider,cloud_region | |
| 2021-12-22T12:36:27,6d18c71e-f1b0-4f2e-b8a5-07165da045c2,codecarbon,3187.4341790676117,0.42607577097711286,1.1584441842770876,USA,USA,nan,Y,aws,us-east-1 | |