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parakeet-ctc-1.1b
NVIDIA`parakeet-ctc-1.1b` is an ASR model that transcribes speech in lower case English alphabet. This model is jointly developed by NVIDIA NeMo and Suno.ai teams. It is an XXL version of FastConformer CTC [1] (around 1.1B parameters) model. See the model architecture section and NeMo documentation for complete architecture details. To train, fine-tune or play with the model you will need to install NVIDIA NeMo. We recommend you install it after you've installed latest PyTorch version. See the NeMo-Speech.cpp documentation for more details.
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View details ↗parakeet-rnnt-0.6b
NVIDIA`parakeet-rnnt-0.6b` is an ASR model that transcribes speech in lower case English alphabet. This model is jointly developed by NVIDIA NeMo and Suno.ai teams. It is an XL version of FastConformer Transducer [1] (around 600M parameters) model. See the model architecture section and NeMo documentation for complete architecture details. License to use this model is covered by the CC-BY-4.0. By downloading the public and release version of the model, you accept the terms and conditions of the CC-BY-4.0 license. For documentation, deployment guides, enterprise-ready APIs, and the latest open models—including Nemotron and other cutting-edge speech, translation, and generative AI—visit the NVIDIA Developer Portal at developer.nvidia.com. Join the community to access tools, support, and resources to accelerate your development with NVIDIA’s NeMo, Riva, NIM, and foundation models.
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View details ↗parakeet-rnnt-1.1b
NVIDIA`parakeet-rnnt-1.1b` is an ASR model that transcribes speech in lower case English alphabet. This model is jointly developed by NVIDIA NeMo and Suno.ai teams. It is an XXL version of FastConformer Transducer [1] (around 1.1B parameters) model. See the model architecture section and NeMo documentation for complete architecture details. For documentation, deployment guides, enterprise-ready APIs, and the latest open models—including Nemotron and other cutting-edge speech, translation, and generative AI—visit the NVIDIA Developer Portal at developer.nvidia.com. Join the community to access tools, support, and resources to accelerate your development with NVIDIA’s NeMo, Riva, NIM, and foundation models. The model is available for use in the NeMo toolkit [3], and can be used as a pre-trained checkpoint for inference or for fine-tuning on another dataset.
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View details ↗parakeet-rnnt-110m-da-dk
NVIDIA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。
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View details ↗parakeet-tdt-0.6b-v2
NVIDIA> **🎉 NEW: Multilingual Parakeet TDT 0.6B V3 is now available!** > 🌍 **25 European Languages** | 🚀 **Enhanced Performance** | 🔗 **Try it here: nvidia/parakeet-tdt-0.6b-v3** `parakeet-tdt-0.6b-v2` is a 600-million-parameter automatic speech recognition (ASR) model designed for high-quality English transcription, featuring support for punctuation, capitalization, and accurate timestamp prediction. Try Demo here: https://huggingface.co/spaces/nvidia/parakeet-tdt-0.6b-v2 This XL variant of the FastConformer [1] architecture integrates the TDT [2] decoder and is trained with full attention, enabling efficient transcription of audio segments up to 24 minutes in a single pass. The model achieves an RTFx of 3380 on the HF-Open-ASR leaderboard with a batch size of 128. Note: *RTFx Performance may vary depending on dataset audio duration and batch size.*
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View details ↗parakeet-tdt-0.6b-v3
NVIDIA`parakeet-tdt-0.6b-v3` is a 600-million-parameter multilingual automatic speech recognition (ASR) model designed for high-throughput speech-to-text transcription. It extends the parakeet-tdt-0.6b-v2 model by expanding language support from English to 25 European languages. The model automatically detects the language of the audio and transcribes it without requiring additional prompting. It is part of a series of models that leverage the Granary [1, 2] multilingual corpus as their primary training dataset. **Supported Languages:** Bulgarian (**bg**), Croatian (**hr**), Czech (**cs**), Danish (**da**), Dutch (**nl**), English (**en**), Estonian (**et**), Finnish (**fi**), French (**fr**), German (**de**), Greek (**el**), Hungarian (**hu**), Italian (**it**), Latvian (**lv**), Lithuanian (**lt**), Maltese (**mt**), Polish (**pl**), Portuguese (**pt**), Romanian (**ro**), Slovak (**sk**), Slovenian (**sl**), Spanish (**es**), Swedish (**sv**), Russian (**ru**), Ukrainian (**uk**) `parakeet-tdt-0.6b-v3`'s key features are built on the foundation of its predecessor, parakeet-tdt-0.6b-v2, and include:
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View details ↗parakeet-tdt-1.1b
NVIDIA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。
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View details ↗parakeet-tdt_ctc-0.6b-ja
NVIDIA`parakeet-tdt_ctc-0.6b-ja` is an ASR model that transcribes Japanese speech with Punctuations. This model is developed by NVIDIA NeMo team. It is an XL version of Hybrid FastConformer [1] TDT-CTC [2] (around 0.6B parameters) model. See the model architecture section and NeMo documentation for complete architecture details. To train, fine-tune or play with the model you will need to install NVIDIA NeMo. We recommend you install it after you've installed latest PyTorch version. The model is available for use in the NeMo Framework [3], and can be used as a pre-trained checkpoint for inference or for fine-tuning on another dataset.
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View details ↗parakeet-tdt_ctc-1.1b
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View details ↗parakeet-tdt_ctc-110m
NVIDIA`parakeet-tdt_ctc-110m` is an ASR model that transcribes speech with Punctuations and Capitalizations of the English alphabet. This model is jointly developed by NVIDIA NeMo and Suno.ai teams. It is a Large version of Hybrid FastConformer [1] TDT-CTC [2] (around 114M parameters) model. This model has been trained with fastconformer architecture with full attention hence this model can transcribe up to 20 minutes of audio in one single pass. This model achieves super fast RTFx values across all datasets, with an average RTFx of ~5300 on Hugging Face leaderboard evaluation sets on A100. See the model architecture section and NeMo documentation for complete architecture details. To train, fine-tune or play with the model you will need to install NVIDIA NeMo. We recommend you install it after you've installed latest PyTorch version. The model is available for use in the NeMo toolkit [3], and can be used as a pre-trained checkpoint for inference or for fine-tuning on another dataset.
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View details ↗parakeet-unified-en-0.6b
NVIDIAParakeet-unified-en-0.6b is an English automatic speech recognition (ASR) model based on transducer architecture (RNN-T) combining both offline and streaming inference (with a minimum latency of 160ms) in one model [1]. It is trained mostly on the English part of the Granary dataset [4], which contains approximately 250,000 hours of US English (en-US) speech across diverse acoustic conditions. The model transcribes speech to English alphabet, spaces, and apostrophes with punctuation and captalization support. Average WER comparison on the HF ASR Leaderboard datasets including offline and streaming inference with different latency values. This model consists of a 🦜 Parakeet (FastConformer) encoder (jointly trained in offline and streaming modes) with an RNN-T decoder. It is designed for offline and streaming speech-to-text applications where latency can be as low as 160ms, such as voice assistants, live captioning, and conversational AI systems. The current inference pipeline supports only buffered streaming (left context is recomputed for each chunk) that can be longer than cache-aware streaming.
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View details ↗PartPacker
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View details ↗personaplex-7b-v1
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View details ↗Phi-4-reasoning-plus-FP8
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