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@@ -32,6 +32,28 @@ slu.decode_file("speechbrain/slu-timers-and-such-direct-librispeech-asr/math.wav
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  ### Inference on GPU
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  To perform inference on the GPU, add `run_opts={"device":"cuda"}` when calling the `from_hparams` method.
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  ### Limitations
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  The SpeechBrain team does not provide any warranty on the performance achieved by this model when used on other datasets.
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@@ -44,7 +66,7 @@ title = {SpeechBrain},
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  year = {2021},
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  publisher = {GitHub},
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  journal = {GitHub repository},
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- howpublished = {\url{https://github.com/speechbrain/speechbrain}},
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  }
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  ```
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  ### Inference on GPU
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  To perform inference on the GPU, add `run_opts={"device":"cuda"}` when calling the `from_hparams` method.
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+ ### Training
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+ The model was trained with SpeechBrain (d254489a).
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+ To train it from scratch follows these steps:
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+ 1. Clone SpeechBrain:
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+ ```bash
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+ git clone https://github.com/speechbrain/speechbrain/
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+ ```
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+ 2. Install it:
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+ ```
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+ cd speechbrain
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+ pip install -r requirements.txt
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+ pip install -e .
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+ ```
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+
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+ 3. Run Training:
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+ ```
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+ cd recipes/timers-and-such/direct
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+ python train.py hparams/train.yaml --data_folder=your_data_folder
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+ ```
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+
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+ You can find our training results (models, logs, etc) [here](https://drive.google.com/drive/folders/18c2anEv8hx-ZjmEN8AdUA8AZziYIidON?usp=sharing)
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+
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  ### Limitations
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  The SpeechBrain team does not provide any warranty on the performance achieved by this model when used on other datasets.
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  year = {2021},
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  publisher = {GitHub},
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  journal = {GitHub repository},
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+ howpublished = {\\url{https://github.com/speechbrain/speechbrain}},
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  }
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  ```
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