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Agora board builds (Model Farm, verified on real boards)

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LICENSE_MODEL_FARM.pdf ADDED
Binary file (71.1 kB). View file
 
NOTICE.md ADDED
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+ # Provenance
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+
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+ Resources are copied without binary changes from the APLUX Model Farm build `SenseVoiceSmall` that Agora verified on real boards (decoded sample check, then measured), pinned by sha256 in SHA256SUMS.
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+
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+ Agora arranges files under targets/<SoC>/<precision>/ and adds model.json. AidLite, AidGen, AidVoice and the Qualcomm QNN runtime are separate dependencies with their own terms.
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+ ---
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+ license: other
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+ license_name: aplux-model-farm
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+ license_link: https://huggingface.co/APLUX-Agora/SenseVoiceSmall/blob/main/LICENSE_MODEL_FARM.pdf
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+ pipeline_tag: automatic-speech-recognition
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+ tags: [Agora, QNN, AIoT, Qualcomm]
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+ ---
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+
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+ # SenseVoiceSmall model resources
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+
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+ SenseVoiceSmall,来自 Model Farm,适配状态按板卡列出。
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+
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+ Board builds that [Agora](https://mega.aidlux.com) runs and measures on real Qualcomm boards. Try it online, without a board: https://mega.aidlux.com/models/sensevoicesmall
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+
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+ | SoC · board | Precisions | Measured on Agora (default precision) |
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+ | --- | --- | --- |
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+ | QCS8550 · 犀牛派 X1 (Rhino Pi X1) | FP16 | RTF 0.055 |
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+
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+ Task: 语音识别. Inputs: audio (audio). Outputs: text (text).
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+
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+ ## Download
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+
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+ ```bash
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+ export AGORA_WORKSPACE="$HOME/my-sensevoicesmall"
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+ export AGORA_SOC='QCS8550'
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+ hf download APLUX-Agora/SenseVoiceSmall \
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+ --include "targets/$AGORA_SOC/*" --local-dir "$AGORA_WORKSPACE/resources"
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+ ```
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+
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+ Each `targets/<SoC>/` holds `model.json` (default precision and variant paths) and one directory per precision. Context binaries are named `model.bin`; multi-file packages are kept as published by Model Farm.
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+
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+ Pre- and post-processing, the runner and an exported project: open the model on Agora and choose “部署指南”, or export any workflow that uses it.
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+
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+ ## Licence and provenance
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+
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+ Source model licence: see the original model's terms.
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+ Converted, deployable resources: APLUX Model Farm License (LICENSE_MODEL_FARM.pdf). See NOTICE.md and SHA256SUMS.
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+ "default_precision": "FP16",
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