节点与集成
NVIDIA Nemotron Chat Model
Use the NVIDIA Nemotron Chat Model node to access NVIDIA Nemotron models with conversational agents1. The node works with Nemotron models hosted on build.nvidia.com and with self-hosted NVIDIA Inference Microservices (NIM).
On this page, you'll find the node parameters for the NVIDIA Nemotron Chat Model node and links to more resources.
Node parameters
Model
Select the Nemotron model to use to generate the completion.
n8n dynamically loads Nemotron models from the endpoint configured in your credential. If n8n can't reach the endpoint, it falls back to a curated list of well-known Nemotron model IDs.
Node options
Use these options to further refine the node's behavior.
Frequency Penalty
Use this option to control the chances of the model repeating itself. Higher values reduce the chance of the model repeating itself.
Maximum Number of Tokens
Enter the maximum number of tokens used, which sets the completion length. Use -1 for the model default.
Response Format
Choose Text or JSON. JSON ensures the model returns valid JSON. When you choose JSON, include the word json in your prompt in the chain or agent.
Presence Penalty
Use this option to control the chances of the model talking about new topics. Higher values increase the chance of the model talking about new topics.
Sampling Temperature
Use this option to control the randomness of the sampling process. A higher temperature creates more diverse sampling, but increases the risk of hallucinations.
Timeout
Enter the maximum request time in milliseconds.
Max Retries
Enter the maximum number of times to retry a request.
Top P
Use this option to set the probability the completion should use. Use a lower value to ignore less probable options.
Templates and examples
Browse NVIDIA Nemotron Chat Model node documentation integration templates or search all templates
Related resources
Refer to NVIDIA's build catalogue for the list of Nemotron models and to the NIM documentation for guidance on self-hosting. As the NVIDIA API is OpenAI-spec compatible, you can refer to LangChain's OpenAI documentation for more information about the underlying client.
View n8n's Advanced AI documentation.
Footnotes
- Back
AI agents are artificial intelligence systems capable of responding to requests, making decisions, and performing real-world tasks for users. They use large language models (LLMs) to interpret user input and make decisions about how to best process requests using the information and resources they have available.
官方原文和授权
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