* Added a `Guidance` method to `LLamaTokenDataArray` which applies classifier free guidance

* Factored out a safer `llama_sample_apply_guidance` method based on spans

* Created a guided sampling demo using the batched executor

* fixed comment, "classifier free" not "context free"

* Rebased onto master and fixed breakage due to changes in `BaseSamplingPipeline`

* Asking user for guidance weight

* Progress bar in batched fork demo

* Improved fork example (using tree display)

* Added proper disposal of resources in batched examples

* Added some more comments in BatchedExecutorGuidance

* - Modified ISamplingPipeline to accept `ReadOnlySpan<float>` of logits directly. This moves responsibility to copy the logits into the pipeline.
 - Added a flag to `BaseSamplingPipeline` indicating if a logit copy is necessary. Skipping it in most cases.

* Fixed `RestoreProtectedTokens` not working if logit processing is skipped

* - Implemented a new greedy sampling pipeline (always sample most likely token)
 - Moved `Grammar` into `BaseSamplingPipeline`
 - Removed "protected tokens" concept from `BaseSamplingPipeline`. Was introducing a lot of incidental complexity.
 - Implemented newline logit save/restore in `DefaultSamplingPipeline` (only place protected tokens was used)

* Implemented pipelines for mirostat v1 and v2

- UserSettings, simplifying the validation/re-ask loop down to one call
 - Program, adding colour to figlet title
 - Batched examples, showing default prompt
 - ExampleRunner, resetting state after running an example

* LLama.Examples: RepoUtils.cs → ConsoleLogger.cs

* LLama.Examples: Examples/Runner.cs → ExampleRunner.cs

* LLama.Examples: delete unused console logger

* LLama.Examples: improve splash screen appearance

the llama_empty_call() no longer shows configuration information on startup, but it will display it automatically the first time a model is engaged

* LLama.Examples: Runner → ExampleRunner

* LLama.Examples: improve model path prompt

The last used model is stored in a config file and is re-used when a blank path is provided

* LLama.Examples: NativeApi.llama_empty_call() at startup

* LLama.Examples: reduce console noise when saving model path

Conversations can be "forked", to create a copy of a conversation at a given point. This allows e.g. prompting a conversation with a system prefix just once and then forking it again and again for each individual conversation. Conversations can also be "rewound" to an earlier state.

Added two new examples, demonstrating forking and rewinding.