Model overview
NVIDIA Nemotron-H-4B-Base-8K is a large language model (LLM) developed by NVIDIA, designed as a completion model for a given piece of text. It uses a hybrid model architecture that consists primarily of Mamba-2 and MLP layers combined with just four Attention layers. The model is pruned and distilled from Nemotron-H-8B-Base-8K using 380B tokens, and features an 8K context length. The supported languages include: English, German, Spanish, French, Italian, Korean, Portuguese, Russian, Japanese, and Chinese. For best performance on a given task, users are encouraged to customize the model using the NeMo Framework suite of customization tools, including Parameter-Efficient Fine-Tuning (P-tuning, Adapters, LoRA, and more), and Model Alignment (SFT, SteerLM, RLHF, and more) using NeMo-Aligner. The model was pruned and distilled from Nemotron-H-Base-8K using our hybrid language model compression technique and then fine-tuned into Nemotron-H-4B-Instruct-128K. For more details, please refer to the paper.
Key features
特点摘要待依据来源补齐,不凭模型名称推断能力。
Limitations & considerations
Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.
Source prices & cost analysis
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Estimate monthly base token costs
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Public benchmarks & run configuration
暂无已采集的可核验公开评分。模型未上榜不代表能力较低。
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Sources & traceability
许可证:other。模型介绍与第三方评测均以原来源的具体版本和方法为准。