The Text Generation Inference is a Rust, Python, and gRPC server specifically designed for text generation inference. It can be self-hosted to power LLM APIs and inference widgets.
Please note that this node does not connect to the Hugging Face Hub, but to a Text Generation Inference Server that can be hosted both locally and remotely.
For more details and information about integrating with the Hugging Face TextGen Inference and setting up a local server, refer to the LangChain documentation.
The URL of the inference server to use, e.g.
Model specific system prompt template. Defaults to "%1". Refer to the Hugging Face Hub model card for information on the correct prompt template.
Model specific prompt template. Defaults to "%1". Refer to the Hugging Face Hub model card for information on the correct prompt template.
The number of top-k tokens to consider when generating text.
The typical probability threshold for generating text.
The repetition penalty to use when generating text.
The maximum number of tokens to generate in the completion.
The token count of your prompt plus max new tokens cannot exceed the model's context length.
Sampling temperature to use, between 0.0 and 100.0. Higher values will make the output more random, while lower values will make it more focused and deterministic.
An alternative to sampling with temperature, where the model considers the results of the tokens (words) with top_p probability mass. Hence, 0.1 means only the tokens comprising the top 10% probability mass are considered.
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