Hugging Face 热门模型第 24 名：nvidia/NVIDIA-Nemotron-3.5-Transcribe-30B-A4B，180 赞，近期下载 338 次。
标签：nemo, safetensors, nemo_speechlm, text2text-generation, nvidia, pytorch, nemotron-3.5, speech, asr, speech-translation, speaker-diarization, audio
README：
NVIDIA-Nemotron-3.5-Transcribe-30B-A4B
Nemotron 3.5 Transcribe is an open-weight, offline speech and audio model for transcription in 40 languages, with support for recordings up to one hour and a 65,536-token context. Its hybrid mixture-of-experts architecture activates approximately 4.3B parameters, including the audio encoder, and it is released in BF16, FP8, and NVFP4 precision.
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Table of contents
Model Overview
Description
NVIDIA Nemotron-3.5-Transcribe is an offline speech and audio model that processes recordings, together with text instructions and optional context, into text responses.
NVIDIA developed this Speech-Augmented Language Model (SALM) for multilingual transcription, speech translation, contextual transcription, speaker-attributed transcription, rich transcription, timestamp prediction, language identification, and audio question answering. The training mixture also includes a small amount of text instruction following and PII tagging/redaction tasks.
This model is ready for commercial or non-commercial use.
Model Summary
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| Total Parameters |
34B (4.3B active), including the audio encoder |
| Architecture |
Mamba-2–Transformer hybrid Mixture of Experts language model with a Parallel Expert Encoder (Transformer ASR encoder and speaker encoder) |
| Precision |
BF16 (full-precision reference weights); FP8 and NVFP4 variants are available |
| Context Length |
65,536 tokens; recordings up to 1 hour |
| Inputs / Outputs |
Audio and text / text, with optional word timestamps |
| Languages |
40; see the language support matrix |
| Tasks |
Transcription in verbatim or written form, contextual transcription, |
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