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add Repeat Penalty description to docs
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ej52 committed Nov 10, 2023
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Expand Up @@ -61,6 +61,7 @@ The language model and additional parameters to fine tune the responses.
| Mirostat ETA | Influences how quickly the algorithm responds to feedback from the generated text. A lower learning rate will result in slower adjustments, while a higher learning rate will make the algorithm more responsive. |
| Mirostat TAU | Controls the balance between coherence and diversity of the output. A lower value will result in more focused and coherent text. |
| Temperature | The temperature of the model. A higher value (e.g., 0.95) will lead to more unexpected results, while a lower value (e.g. 0.5) will be more deterministic results. |
| Repeat Penalty | Sets how strongly to penalize repetitions. A higher value (e.g., 1.5) will penalize repetitions more strongly, while a lower value (e.g., 0.9) will be more lenient. |
| Top K | Reduces the probability of generating nonsense. A higher value (e.g. 100) will give more diverse answers, while a lower value (e.g. 10) will be more conservative. |
| Top P | Works together with top-k. A higher value (e.g., 0.95) will lead to more diverse text, while a lower value (e.g., 0.5) will generate more focused and conservative text. | |

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7 changes: 1 addition & 6 deletions info.md
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[![GitHub Release](https://img.shields.io/github/release/ej52/hass-ollama-conversation.svg?style=flat-square)](https://github.com/ej52/hass-ollama-conversation/releases)
[![Downloads](https://img.shields.io/github/downloads/ej52/hass-ollama-conversation/total?style=flat-square)](https://github.com/ej52/hass-ollama-conversation/releases)
[![Build Status](https://img.shields.io/github/actions/workflow/status/ej52/hass-ollama-conversation/validate.yml?style=flat-square)](https://github.com/ej52/hass-ollama-conversation/actions/workflows/validate.yaml)
[![License](https://img.shields.io/github/license/ej52/hass-ollama-conversation.svg?style=flat-square)](LICENSE)
[![hacs](https://img.shields.io/badge/HACS-default-orange.svg?style=flat-square)](https://hacs.xyz)

# Ollama Conversation

The Ollama integration adds a conversation agent powered by [Ollama][ollama] in Home Assistant.
Expand Down Expand Up @@ -42,6 +36,7 @@ The language model and additional parameters to fine tune the responses.
| Mirostat ETA | Influences how quickly the algorithm responds to feedback from the generated text. A lower learning rate will result in slower adjustments, while a higher learning rate will make the algorithm more responsive. |
| Mirostat TAU | Controls the balance between coherence and diversity of the output. A lower value will result in more focused and coherent text. |
| Temperature | The temperature of the model. A higher value (e.g., 0.95) will lead to more unexpected results, while a lower value (e.g. 0.5) will be more deterministic results. |
| Repeat Penalty | Sets how strongly to penalize repetitions. A higher value (e.g., 1.5) will penalize repetitions more strongly, while a lower value (e.g., 0.9) will be more lenient. |
| Top K | Reduces the probability of generating nonsense. A higher value (e.g. 100) will give more diverse answers, while a lower value (e.g. 10) will be more conservative. |
| Top P | Works together with top-k. A higher value (e.g., 0.95) will lead to more diverse text, while a lower value (e.g., 0.5) will generate more focused and conservative text. |

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