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AI 모델 탐색 9

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moonshine-base

moonshine-ai

This is the model card for running the automatic speech recognition (ASR) models (Moonshine models) trained and released by Useful Sensors. Following Model Cards for Model Reporting (Mitchell et al.), we're providing some information about the automatic speech recognition model. More information on how these models were trained and evaluated can be found in the paper. Note, a lot of the text has been copied verbatim from the model card for the Whisper model developed by OpenAI, because both models serve identical purposes, and carry identical risks. Moonshine is supported in Hugging Face 🤗 Transformers. To run the model, first install the Transformers library. For this example, we'll also install 🤗 Datasets to load toy audio dataset from the Hugging Face Hub, and 🤗 Accelerate to reduce the model loading time:

번역 대기 중 · 원문 표시

음성 인식

입력 오디오→ 출력 텍스트

요금 미확인멀티모달 및 채널 요금 별도 확인

자세히 보기 ↗

비교 추가출처 / 문서 ↗

moonshine-base-ko

moonshine-ai

基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。

기본 정보 등록 · 상세 정보 보완 예정

음성 인식

입력 오디오→ 출력 텍스트

요금 미확인멀티모달 및 채널 요금 별도 확인

자세히 보기 ↗

비교 추가출처 / 문서 ↗

moonshine-streaming-medium

moonshine-ai

This is the model card for the Moonshine Streaming automatic speech recognition (ASR) models trained and released by Useful Sensors. Moonshine Streaming pairs a lightweight 50~Hz audio frontend with a sliding-window Transformer encoder to deliver low-latency streaming ASR on edge-class hardware. The encoder uses bounded local attention and no positional embeddings (an "ergodic" encoder), while an adapter injects positional information before a standard autoregressive decoder. This model card follows the recommendations from Model Cards for Model Reporting (Mitchell et al.). See the paper draft in this repository for full details. Moonshine Streaming is supported by the Moonshine Voice framework for edge devices and in Hugging Face Transformers. The following example matches the standard seq2seq ASR API and uses the streaming model checkpoint:

번역 대기 중 · 원문 표시

음성 인식

입력 오디오→ 출력 텍스트

요금 미확인멀티모달 및 채널 요금 별도 확인

자세히 보기 ↗

비교 추가출처 / 문서 ↗

moonshine-streaming-small

moonshine-ai

This is the model card for the Moonshine Streaming automatic speech recognition (ASR) models trained and released by Useful Sensors. Moonshine Streaming pairs a lightweight 50~Hz audio frontend with a sliding-window Transformer encoder to deliver low-latency streaming ASR on edge-class hardware. The encoder uses bounded local attention and no positional embeddings (an "ergodic" encoder), while an adapter injects positional information before a standard autoregressive decoder. This model card follows the recommendations from Model Cards for Model Reporting (Mitchell et al.). See the paper draft in this repository for full details. Moonshine Streaming is supported in Hugging Face Transformers. The following example matches the standard seq2seq ASR API and uses the streaming model checkpoint:

번역 대기 중 · 원문 표시

음성 인식

입력 오디오→ 출력 텍스트

요금 미확인멀티모달 및 채널 요금 별도 확인

자세히 보기 ↗

비교 추가출처 / 문서 ↗

moonshine-streaming-tiny

moonshine-ai

This is the model card for the Moonshine Streaming automatic speech recognition (ASR) models trained and released by Useful Sensors. Moonshine Streaming pairs a lightweight 50~Hz audio frontend with a sliding-window Transformer encoder to deliver low-latency streaming ASR on edge-class hardware. The encoder uses bounded local attention and no positional embeddings (an "ergodic" encoder), while an adapter injects positional information before a standard autoregressive decoder. This model card follows the recommendations from Model Cards for Model Reporting (Mitchell et al.). See the paper draft in this repository for full details. Moonshine Streaming is supported in Hugging Face Transformers. The following example matches the standard seq2seq ASR API and uses the streaming model checkpoint:

번역 대기 중 · 원문 표시

음성 인식

입력 오디오→ 출력 텍스트

요금 미확인멀티모달 및 채널 요금 별도 확인

자세히 보기 ↗

비교 추가출처 / 문서 ↗