From 88dbb0ba10cd32ea4f3aee0dc1c84ba0238d8a46 Mon Sep 17 00:00:00 2001 From: Deborah Date: Mon, 29 Apr 2024 11:35:48 +0100 Subject: [PATCH] Apply suggestions from code review --- .../sub-nodes/n8n-nodes-langchain.lmchatollama.md | 12 ++++++------ 1 file changed, 6 insertions(+), 6 deletions(-) diff --git a/docs/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatollama.md b/docs/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatollama.md index 782116dfb..d2649e413 100644 --- a/docs/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatollama.md +++ b/docs/integrations/builtin/cluster-nodes/sub-nodes/n8n-nodes-langchain.lmchatollama.md @@ -26,7 +26,7 @@ For usage examples and templates to help you get started, refer to n8n's [Ollama ## Node options * **Sampling Temperature**: controls the randomness of the sampling process. A higher temperature creates more diverse sampling, but increases the risk of hallucinations. -* **Top K**: limits the number of highest probability vocabulary tokens to consider at each step. A higher value increases diversity but may reduce coherence. Set to -1 to disable. Valid range is between -1 and 100. +* **Top K**: limits the number of highest probability vocabulary tokens to consider at each step. A higher value increases diversity but may reduce coherence. Set to `-1` to disable. Valid range is between -1 and 100. * **Top P**: chooses from the smallest possible set of tokens whose cumulative probability exceeds the probability top_p. Helps generate more human-like text by reducing repetitions. Valid range is between 0 and 1. * **Frequency Penalty**: adjusts the penalty for tokens that have already appeared in the generated text. Higher values discourage repetition. Must be a non-negative number. * **Keep Alive**: specifies the duration to keep the loaded model in memory after use. Useful for frequently used models. Format: 1h30m (1 hour 30 minutes). @@ -34,16 +34,16 @@ For usage examples and templates to help you get started, refer to n8n's [Ollama * **Main GPU ID**: specifies the ID of the GPU to use for the main computation. Only change this if you have multiple GPUs. * **Context Batch Size**: sets the batch size for prompt processing. Larger batch sizes may improve generation speed but increase memory usage. * **Context Length**: the maximum number of tokens to use as context for generating the next token. Smaller values reduce memory usage, while larger values provide more context to the model. -* **Number of GPUs**: specifies the number of GPUs to use for parallel processing. Set to -1 for auto-detection. -* **Max Tokens to Generate**: the maximum number of tokens to generate. Set to -1 for no limit. Be cautious when setting this to a large value, as it can lead to very long outputs. -* **Number of CPU Threads**: specifies the number of CPU threads to use for processing. Set to 0 for auto-detection. +* **Number of GPUs**: specifies the number of GPUs to use for parallel processing. Set to `-1` for auto-detection. +* **Max Tokens to Generate**: the maximum number of tokens to generate. Set to `-1` for no limit. Be cautious when setting this to a large value, as it can lead to very long outputs. +* **Number of CPU Threads**: specifies the number of CPU threads to use for processing. Set to `0` for auto-detection. * **Penalize Newlines**: whether the model will be less likely to generate newline characters, encouraging longer continuous sequences of text. * **Presence Penalty**: adjusts the penalty for tokens based on their presence in the generated text so far. Positive values penalize tokens that have already appeared, encouraging diversity. -* **Repetition Penalty**: adjusts the penalty factor for repeated tokens. Higher values more strongly discourage repetition. Set to 1.0 to disable repetition penalty. +* **Repetition Penalty**: adjusts the penalty factor for repeated tokens. Higher values more strongly discourage repetition. Set to `1.0` to disable repetition penalty. * **Use Memory Locking**: whether to lock the model in memory to prevent swapping. This can improve performance but requires sufficient available memory. * **Use Memory Mapping**: whether to use memory mapping for loading the model. This can reduce memory usage but may impact performance. Recommended to keep enabled. * **Load Vocabulary Only**: whether to only load the model vocabulary without the weights. Useful for quickly testing tokenization. -* **Output Format**: specifies the format of the API response. Choose between 'Default' and 'JSON'. +* **Output Format**: specifies the format of the API response. Choose between **Default** and **JSON**. ## Related resources