Instructions to use sanchit-gandhi/flax-wav2vec2-2-bart-large-gs-baseline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sanchit-gandhi/flax-wav2vec2-2-bart-large-gs-baseline with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="sanchit-gandhi/flax-wav2vec2-2-bart-large-gs-baseline")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("sanchit-gandhi/flax-wav2vec2-2-bart-large-gs-baseline") model = AutoModelForMultimodalLM.from_pretrained("sanchit-gandhi/flax-wav2vec2-2-bart-large-gs-baseline") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7f5a4b6b3f963872fcf7715008ecadf0ae8987bf11fd44af6a17d1d90aaac0f6
- Size of remote file:
- 2.35 GB
- SHA256:
- 04aec7bb8b27060f59fa1b4fa83d659b02b7e5b88f353003fba838796b5db8ad
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