Instructions to use Bagus/wav2vec2-2-bart-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bagus/wav2vec2-2-bart-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Bagus/wav2vec2-2-bart-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSpeechSeq2Seq tokenizer = AutoTokenizer.from_pretrained("Bagus/wav2vec2-2-bart-base") model = AutoModelForSpeechSeq2Seq.from_pretrained("Bagus/wav2vec2-2-bart-base") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForSpeechSeq2Seq
tokenizer = AutoTokenizer.from_pretrained("Bagus/wav2vec2-2-bart-base")
model = AutoModelForSpeechSeq2Seq.from_pretrained("Bagus/wav2vec2-2-bart-base")Quick Links
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Check out the documentation for more information.
This model is use to warmup training other models.
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Bagus/wav2vec2-2-bart-base")