Instructions to use esc-bench/wav2vec2-aed-chime4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use esc-bench/wav2vec2-aed-chime4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="esc-bench/wav2vec2-aed-chime4")# Load model directly from transformers import AutoTokenizer, AutoModelForSpeechSeq2Seq tokenizer = AutoTokenizer.from_pretrained("esc-bench/wav2vec2-aed-chime4") model = AutoModelForSpeechSeq2Seq.from_pretrained("esc-bench/wav2vec2-aed-chime4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Sanchit Gandhi commited on
Commit ·
1686843
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Parent(s): ff7e448
Add scripts and weights
Browse files
README.md
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- esc
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datasets:
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- chime4
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```python
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#!/usr/bin/env bash
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python run_flax_speech_recognition_seq2seq.py \
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- esc
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datasets:
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- chime4
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To reproduce this run, execute:
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```python
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#!/usr/bin/env bash
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python run_flax_speech_recognition_seq2seq.py \
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