Automatic Speech Recognition
Transformers
Safetensors
English
joint_aed_ctc_speech-encoder-decoder
custom_code
Eval Results (legacy)
Instructions to use BUT-FIT/DeCRED-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BUT-FIT/DeCRED-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="BUT-FIT/DeCRED-base", trust_remote_code=True)# Load model directly from transformers import AutoModelForSpeechSeq2Seq model = AutoModelForSpeechSeq2Seq.from_pretrained("BUT-FIT/DeCRED-base", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update train.sh
Browse files
train.sh
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#!/usr/bin/bash
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#SBATCH --job-name
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#SBATCH --account OPEN-28-57
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#SBATCH --partition qgpu
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#SBATCH --nodes=6
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#!/usr/bin/bash
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#SBATCH --job-name DeCRED
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#SBATCH --account OPEN-28-57
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#SBATCH --partition qgpu
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#SBATCH --nodes=6
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