docs: Add Mirostat Explanation (#7128)

docs/03 - Parameters Tab.md

@@ -51,10 +51,12 @@ For more information about the parameters, the [transformers documentation](http
 * **guidance_scale**: The main parameter for Classifier-Free Guidance (CFG). [The paper](https://arxiv.org/pdf/2306.17806.pdf) suggests that 1.5 is a good value. It can be used in conjunction with a negative prompt or not.
 * **Negative prompt**: Only used when `guidance_scale != 1`. It is most useful for instruct models and custom system messages. You place your full prompt in this field with the system message replaced with the default one for the model (like "You are Llama, a helpful assistant...") to make the model pay more attention to your custom system message.
 * **penalty_alpha**: Contrastive Search is enabled by setting this to greater than zero and unchecking "do_sample". It should be used with a low value of top_k, for instance, top_k = 4.
-* **mirostat_mode**: Activates the Mirostat sampling technique. It aims to control perplexity during sampling. See the [paper](https://arxiv.org/abs/2007.14966).
-* **mirostat_tau**: No idea, see the paper for details. According to the Preset Arena, 8 is a good value. 
-* **mirostat_eta**: No idea, see the paper for details. According to the Preset Arena, 0.1 is a good value.
+* **mirostat_mode**: Activates Mirostat sampling, an adaptive decoding method that dynamically controls output perplexity for higher-quality text generation. 0 is disabled. 1 is the classic Mirostat algorithm described in [the paper](https://arxiv.org/abs/2007.14966), but can be less stable, or “wobbly,” and produce less coherent text. 2 is the improved version that is more stable and has lower perplexity, recommended for most use cases. 
+*Note: Use either mirostat or dynamic_temperature, not both at the same time.*
+* **mirostat_tau**: Target perplexity for Mirostat sampling. Controls how “surprising” the text is. Higher values = more diverse, lower = more predictable. Preset Arena suggests 8 as a good value.
+* **mirostat_eta**: Learning rate for Mirostat’s perplexity adjustment. Higher values = adapts faster but less stable, lower values = slower but more stable. Preset Arena suggests 0.1 as a good value.
 * **dynamic_temperature**: Activates Dynamic Temperature. This modifies temperature to range between "dynatemp_low" (minimum) and "dynatemp_high" (maximum), with an entropy-based scaling. The steepness of the curve is controlled by "dynatemp_exponent". 
+*Note: Use either dynamic_temperature or mirostat, not both at the same time.*
 * **smoothing_factor**: Activates Quadratic Sampling. When `0 < smoothing_factor < 1`, the logits distribution becomes flatter. When `smoothing_factor > 1`, it becomes more peaked.
 * **temperature_last**: Makes temperature the last sampler instead of the first. With this, you can remove low probability tokens with a sampler like min_p and then use a high temperature to make the model creative without losing coherency. Note: this parameter takes precedence over "Sampler priority". That means that `temperature`/`dynamic_temperature`/`quadratic_sampling` will be removed from wherever they are and moved to the end of the stack.
 * **do_sample**: When unchecked, sampling is entirely disabled, and greedy decoding is used instead (the most likely token is always picked).