Instructions to use wmoto-ai/moonshine-tiny-ja-ONNX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers.js
How to use wmoto-ai/moonshine-tiny-ja-ONNX with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('automatic-speech-recognition', 'wmoto-ai/moonshine-tiny-ja-ONNX');
Upload folder using huggingface_hub
Browse files- decoder_model.onnx → onnx/decoder_model.onnx +0 -0
- decoder_model_merged.onnx → onnx/decoder_model_merged.onnx +0 -0
- onnx/decoder_model_merged_quantized.onnx +3 -0
- decoder_with_past_model.onnx → onnx/decoder_with_past_model.onnx +0 -0
- encoder_model.onnx → onnx/encoder_model.onnx +0 -0
- onnx/encoder_model_quantized.onnx +3 -0
decoder_model.onnx → onnx/decoder_model.onnx
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decoder_model_merged.onnx → onnx/decoder_model_merged.onnx
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onnx/decoder_model_merged_quantized.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:37915e1a47a3e8aa1165691e862ab8b4ba80ad404cc2401b70aa819973eaac98
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size 116312428
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decoder_with_past_model.onnx → onnx/decoder_with_past_model.onnx
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encoder_model.onnx → onnx/encoder_model.onnx
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onnx/encoder_model_quantized.onnx
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version https://git-lfs.github.com/spec/v1
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oid sha256:88559bbbc95666f2c2a45e878c15edf523b9e6eabca7eb3572178ff77e1d49ae
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size 30962847
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