Instructions to use KrorngAI/TrorYongASR2-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KrorngAI/TrorYongASR2-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="KrorngAI/TrorYongASR2-small")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("KrorngAI/TrorYongASR2-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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##### Length Predictor
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To make TrorYongASR2 as lightweight as possible, length predictor infers the length of text sequence conditioned directly on the audio encoding.
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TrorYongASR2 limits the output text to
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Therefore, length predictor's head is a linear layer with a softcap as the following:
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$$
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##### Length Predictor
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To make TrorYongASR2 as lightweight as possible, length predictor infers the length of text sequence conditioned directly on the audio encoding.
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TrorYongASR2 limits the output text to $``448``$ tokens.
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Therefore, length predictor's head is a linear layer with a softcap as the following:
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$$
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