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  <a href="#llamatokendataarraymemoryllamatokendata-boolean" class="md-nav__link">
    LLamaTokenDataArray(Memory&lt;LLamaTokenData&gt;, Boolean)
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    <nav class="md-nav" aria-label="LLamaTokenDataArray(Memory<LLamaTokenData>, Boolean)">
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    Create(ReadOnlySpan&lt;Single&gt;)
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    Parameters
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  <a href="#overwritelogitsreadonlyspanvaluetuplellamatoken-single" class="md-nav__link">
    OverwriteLogits(ReadOnlySpan&lt;ValueTuple&lt;LLamaToken, Single&gt;&gt;)
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          <li class="md-nav__item">
  <a href="#applygrammarsafellamacontexthandle-safellamagrammarhandle" class="md-nav__link">
    ApplyGrammar(SafeLLamaContextHandle, SafeLLamaGrammarHandle)
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          <li class="md-nav__item">
  <a href="#topksafellamacontexthandle-int32-uint64" class="md-nav__link">
    TopK(SafeLLamaContextHandle, Int32, UInt64)
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  <a href="#toppsafellamacontexthandle-single-uint64" class="md-nav__link">
    TopP(SafeLLamaContextHandle, Single, UInt64)
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  <a href="#minpsafellamacontexthandle-single-uint64" class="md-nav__link">
    MinP(SafeLLamaContextHandle, Single, UInt64)
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  <a href="#tailfreesafellamacontexthandle-single-uint64" class="md-nav__link">
    TailFree(SafeLLamaContextHandle, Single, UInt64)
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    LocallyTypical(SafeLLamaContextHandle, Single, UInt64)
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  <a href="#repetitionpenaltysafellamacontexthandle-readonlyspanllamatoken-single-single-single" class="md-nav__link">
    RepetitionPenalty(SafeLLamaContextHandle, ReadOnlySpan&lt;LLamaToken&gt;, Single, Single, Single)
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  <a href="#guidancesafellamacontexthandle-readonlyspansingle-single" class="md-nav__link">
    Guidance(SafeLLamaContextHandle, ReadOnlySpan&lt;Single&gt;, Single)
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  <a href="#temperaturesafellamacontexthandle-single" class="md-nav__link">
    Temperature(SafeLLamaContextHandle, Single)
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  <a href="#softmaxsafellamacontexthandle" class="md-nav__link">
    Softmax(SafeLLamaContextHandle)
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  <a href="#sampletokensafellamacontexthandle" class="md-nav__link">
    SampleToken(SafeLLamaContextHandle)
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  <a href="#sampletokengreedysafellamacontexthandle" class="md-nav__link">
    SampleTokenGreedy(SafeLLamaContextHandle)
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    Parameters
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          <li class="md-nav__item">
  <a href="#sampletokenmirostatsafellamacontexthandle-single-single-int32-single" class="md-nav__link">
    SampleTokenMirostat(SafeLLamaContextHandle, Single, Single, Int32, Single&amp;)
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          <li class="md-nav__item">
  <a href="#sampletokenmirostat2safellamacontexthandle-single-single-single" class="md-nav__link">
    SampleTokenMirostat2(SafeLLamaContextHandle, Single, Single, Single&amp;)
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    <nav class="md-nav" aria-label="SampleTokenMirostat2(SafeLLamaContextHandle, Single, Single, Single&)">
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<h1 id="llamatokendataarray">LLamaTokenDataArray</h1>
<p>Namespace: LLama.Native</p>
<p>Contains an array of LLamaTokenData, potentially sorted.</p>
<pre><code class="language-csharp">public struct LLamaTokenDataArray
</code></pre>
<p>Inheritance <a href="https://docs.microsoft.com/en-us/dotnet/api/system.object">Object</a> → <a href="https://docs.microsoft.com/en-us/dotnet/api/system.valuetype">ValueType</a> → <a href="./">LLamaTokenDataArray</a></p>
<h2 id="fields">Fields</h2>
<h3 id="data"><strong>data</strong></h3>
<p>The LLamaTokenData</p>
<pre><code class="language-csharp">public Memory&lt;LLamaTokenData&gt; data;
</code></pre>
<h3 id="sorted"><strong>sorted</strong></h3>
<p>Indicates if <code>data</code> is sorted by logits in descending order. If this is false the token data is in <em>no particular order</em>.</p>
<pre><code class="language-csharp">public bool sorted;
</code></pre>
<h2 id="constructors">Constructors</h2>
<h3 id="llamatokendataarraymemoryllamatokendata-boolean"><strong>LLamaTokenDataArray(Memory&lt;LLamaTokenData&gt;, Boolean)</strong></h3>
<p>Create a new LLamaTokenDataArray</p>
<pre><code class="language-csharp">LLamaTokenDataArray(Memory&lt;LLamaTokenData&gt; tokens, bool isSorted)
</code></pre>
<h4 id="parameters">Parameters</h4>
<p><code>tokens</code> <a href="https://docs.microsoft.com/en-us/dotnet/api/system.memory-1">Memory&lt;LLamaTokenData&gt;</a><br></p>
<p><code>isSorted</code> <a href="https://docs.microsoft.com/en-us/dotnet/api/system.boolean">Boolean</a><br></p>
<h2 id="methods">Methods</h2>
<h3 id="createreadonlyspansingle"><strong>Create(ReadOnlySpan&lt;Single&gt;)</strong></h3>
<p>Create a new LLamaTokenDataArray, copying the data from the given logits</p>
<pre><code class="language-csharp">LLamaTokenDataArray Create(ReadOnlySpan&lt;float&gt; logits)
</code></pre>
<h4 id="parameters_1">Parameters</h4>
<p><code>logits</code> <a href="https://docs.microsoft.com/en-us/dotnet/api/system.readonlyspan-1">ReadOnlySpan&lt;Single&gt;</a><br></p>
<h4 id="returns">Returns</h4>
<p><a href="./">LLamaTokenDataArray</a><br></p>
<h3 id="overwritelogitsreadonlyspanvaluetuplellamatoken-single"><strong>OverwriteLogits(ReadOnlySpan&lt;ValueTuple&lt;LLamaToken, Single&gt;&gt;)</strong></h3>
<p>Overwrite the logit values for all given tokens</p>
<pre><code class="language-csharp">void OverwriteLogits(ReadOnlySpan&lt;ValueTuple&lt;LLamaToken, float&gt;&gt; values)
</code></pre>
<h4 id="parameters_2">Parameters</h4>
<p><code>values</code> <a href="https://docs.microsoft.com/en-us/dotnet/api/system.readonlyspan-1">ReadOnlySpan&lt;ValueTuple&lt;LLamaToken, Single&gt;&gt;</a><br>
tuples of token and logit value to overwrite</p>
<h3 id="applygrammarsafellamacontexthandle-safellamagrammarhandle"><strong>ApplyGrammar(SafeLLamaContextHandle, SafeLLamaGrammarHandle)</strong></h3>
<p>Apply grammar rules to candidate tokens</p>
<pre><code class="language-csharp">void ApplyGrammar(SafeLLamaContextHandle ctx, SafeLLamaGrammarHandle grammar)
</code></pre>
<h4 id="parameters_3">Parameters</h4>
<p><code>ctx</code> <a href="../llama.native.safellamacontexthandle/">SafeLLamaContextHandle</a><br></p>
<p><code>grammar</code> <a href="../llama.native.safellamagrammarhandle/">SafeLLamaGrammarHandle</a><br></p>
<h3 id="topksafellamacontexthandle-int32-uint64"><strong>TopK(SafeLLamaContextHandle, Int32, UInt64)</strong></h3>
<p>Top-K sampling described in academic paper "The Curious Case of Neural Text Degeneration" https://arxiv.org/abs/1904.09751</p>
<pre><code class="language-csharp">void TopK(SafeLLamaContextHandle context, int k, ulong minKeep)
</code></pre>
<h4 id="parameters_4">Parameters</h4>
<p><code>context</code> <a href="../llama.native.safellamacontexthandle/">SafeLLamaContextHandle</a><br></p>
<p><code>k</code> <a href="https://docs.microsoft.com/en-us/dotnet/api/system.int32">Int32</a><br>
Number of tokens to keep</p>
<p><code>minKeep</code> <a href="https://docs.microsoft.com/en-us/dotnet/api/system.uint64">UInt64</a><br>
Minimum number to keep</p>
<h3 id="toppsafellamacontexthandle-single-uint64"><strong>TopP(SafeLLamaContextHandle, Single, UInt64)</strong></h3>
<p>Nucleus sampling described in academic paper "The Curious Case of Neural Text Degeneration" https://arxiv.org/abs/1904.09751</p>
<pre><code class="language-csharp">void TopP(SafeLLamaContextHandle context, float p, ulong minKeep)
</code></pre>
<h4 id="parameters_5">Parameters</h4>
<p><code>context</code> <a href="../llama.native.safellamacontexthandle/">SafeLLamaContextHandle</a><br></p>
<p><code>p</code> <a href="https://docs.microsoft.com/en-us/dotnet/api/system.single">Single</a><br></p>
<p><code>minKeep</code> <a href="https://docs.microsoft.com/en-us/dotnet/api/system.uint64">UInt64</a><br></p>
<h3 id="minpsafellamacontexthandle-single-uint64"><strong>MinP(SafeLLamaContextHandle, Single, UInt64)</strong></h3>
<p>Minimum P sampling as described in https://github.com/ggerganov/llama.cpp/pull/3841</p>
<pre><code class="language-csharp">void MinP(SafeLLamaContextHandle context, float p, ulong minKeep)
</code></pre>
<h4 id="parameters_6">Parameters</h4>
<p><code>context</code> <a href="../llama.native.safellamacontexthandle/">SafeLLamaContextHandle</a><br></p>
<p><code>p</code> <a href="https://docs.microsoft.com/en-us/dotnet/api/system.single">Single</a><br>
All tokens with probability greater than this will be kept</p>
<p><code>minKeep</code> <a href="https://docs.microsoft.com/en-us/dotnet/api/system.uint64">UInt64</a><br></p>
<h3 id="tailfreesafellamacontexthandle-single-uint64"><strong>TailFree(SafeLLamaContextHandle, Single, UInt64)</strong></h3>
<p>Tail Free Sampling described in https://www.trentonbricken.com/Tail-Free-Sampling/.</p>
<pre><code class="language-csharp">void TailFree(SafeLLamaContextHandle context, float z, ulong min_keep)
</code></pre>
<h4 id="parameters_7">Parameters</h4>
<p><code>context</code> <a href="../llama.native.safellamacontexthandle/">SafeLLamaContextHandle</a><br></p>
<p><code>z</code> <a href="https://docs.microsoft.com/en-us/dotnet/api/system.single">Single</a><br></p>
<p><code>min_keep</code> <a href="https://docs.microsoft.com/en-us/dotnet/api/system.uint64">UInt64</a><br></p>
<h3 id="locallytypicalsafellamacontexthandle-single-uint64"><strong>LocallyTypical(SafeLLamaContextHandle, Single, UInt64)</strong></h3>
<p>Locally Typical Sampling implementation described in the paper https://arxiv.org/abs/2202.00666.</p>
<pre><code class="language-csharp">void LocallyTypical(SafeLLamaContextHandle context, float p, ulong min_keep)
</code></pre>
<h4 id="parameters_8">Parameters</h4>
<p><code>context</code> <a href="../llama.native.safellamacontexthandle/">SafeLLamaContextHandle</a><br></p>
<p><code>p</code> <a href="https://docs.microsoft.com/en-us/dotnet/api/system.single">Single</a><br></p>
<p><code>min_keep</code> <a href="https://docs.microsoft.com/en-us/dotnet/api/system.uint64">UInt64</a><br></p>
<h3 id="repetitionpenaltysafellamacontexthandle-readonlyspanllamatoken-single-single-single"><strong>RepetitionPenalty(SafeLLamaContextHandle, ReadOnlySpan&lt;LLamaToken&gt;, Single, Single, Single)</strong></h3>
<p>Repetition penalty described in CTRL academic paper https://arxiv.org/abs/1909.05858, with negative logit fix.
 Frequency and presence penalties described in OpenAI API https://platform.openai.com/docs/api-reference/parameter-details.</p>
<pre><code class="language-csharp">void RepetitionPenalty(SafeLLamaContextHandle context, ReadOnlySpan&lt;LLamaToken&gt; last_tokens, float penalty_repeat, float penalty_freq, float penalty_present)
</code></pre>
<h4 id="parameters_9">Parameters</h4>
<p><code>context</code> <a href="../llama.native.safellamacontexthandle/">SafeLLamaContextHandle</a><br></p>
<p><code>last_tokens</code> <a href="https://docs.microsoft.com/en-us/dotnet/api/system.readonlyspan-1">ReadOnlySpan&lt;LLamaToken&gt;</a><br></p>
<p><code>penalty_repeat</code> <a href="https://docs.microsoft.com/en-us/dotnet/api/system.single">Single</a><br></p>
<p><code>penalty_freq</code> <a href="https://docs.microsoft.com/en-us/dotnet/api/system.single">Single</a><br></p>
<p><code>penalty_present</code> <a href="https://docs.microsoft.com/en-us/dotnet/api/system.single">Single</a><br></p>
<h3 id="guidancesafellamacontexthandle-readonlyspansingle-single"><strong>Guidance(SafeLLamaContextHandle, ReadOnlySpan&lt;Single&gt;, Single)</strong></h3>
<p>Apply classifier-free guidance to the logits as described in academic paper "Stay on topic with Classifier-Free Guidance" https://arxiv.org/abs/2306.17806</p>
<pre><code class="language-csharp">void Guidance(SafeLLamaContextHandle context, ReadOnlySpan&lt;float&gt; guidanceLogits, float guidance)
</code></pre>
<h4 id="parameters_10">Parameters</h4>
<p><code>context</code> <a href="../llama.native.safellamacontexthandle/">SafeLLamaContextHandle</a><br></p>
<p><code>guidanceLogits</code> <a href="https://docs.microsoft.com/en-us/dotnet/api/system.readonlyspan-1">ReadOnlySpan&lt;Single&gt;</a><br>
Logits extracted from a separate context from the same model.
 Other than a negative prompt at the beginning, it should have all generated and user input tokens copied from the main context.</p>
<p><code>guidance</code> <a href="https://docs.microsoft.com/en-us/dotnet/api/system.single">Single</a><br>
Guidance strength. 0 means no guidance, higher values applies stronger guidance</p>
<h3 id="temperaturesafellamacontexthandle-single"><strong>Temperature(SafeLLamaContextHandle, Single)</strong></h3>
<p>Sample with temperature.
 As temperature increases, the prediction becomes more diverse but also vulnerable to hallucinations -- generating tokens that are sensible but not factual</p>
<pre><code class="language-csharp">void Temperature(SafeLLamaContextHandle context, float temp)
</code></pre>
<h4 id="parameters_11">Parameters</h4>
<p><code>context</code> <a href="../llama.native.safellamacontexthandle/">SafeLLamaContextHandle</a><br></p>
<p><code>temp</code> <a href="https://docs.microsoft.com/en-us/dotnet/api/system.single">Single</a><br></p>
<h3 id="softmaxsafellamacontexthandle"><strong>Softmax(SafeLLamaContextHandle)</strong></h3>
<p>Sorts candidate tokens by their logits in descending order and calculate probabilities based on logits.</p>
<pre><code class="language-csharp">void Softmax(SafeLLamaContextHandle context)
</code></pre>
<h4 id="parameters_12">Parameters</h4>
<p><code>context</code> <a href="../llama.native.safellamacontexthandle/">SafeLLamaContextHandle</a><br></p>
<h3 id="sampletokensafellamacontexthandle"><strong>SampleToken(SafeLLamaContextHandle)</strong></h3>
<p>Randomly selects a token from the candidates based on their probabilities.</p>
<pre><code class="language-csharp">LLamaToken SampleToken(SafeLLamaContextHandle context)
</code></pre>
<h4 id="parameters_13">Parameters</h4>
<p><code>context</code> <a href="../llama.native.safellamacontexthandle/">SafeLLamaContextHandle</a><br></p>
<h4 id="returns_1">Returns</h4>
<p><a href="../llama.native.llamatoken/">LLamaToken</a><br></p>
<h3 id="sampletokengreedysafellamacontexthandle"><strong>SampleTokenGreedy(SafeLLamaContextHandle)</strong></h3>
<p>Selects the token with the highest probability.</p>
<pre><code class="language-csharp">LLamaToken SampleTokenGreedy(SafeLLamaContextHandle context)
</code></pre>
<h4 id="parameters_14">Parameters</h4>
<p><code>context</code> <a href="../llama.native.safellamacontexthandle/">SafeLLamaContextHandle</a><br></p>
<h4 id="returns_2">Returns</h4>
<p><a href="../llama.native.llamatoken/">LLamaToken</a><br></p>
<h3 id="sampletokenmirostatsafellamacontexthandle-single-single-int32-single"><strong>SampleTokenMirostat(SafeLLamaContextHandle, Single, Single, Int32, Single&amp;)</strong></h3>
<p>Mirostat 1.0 algorithm described in the paper https://arxiv.org/abs/2007.14966. Uses tokens instead of words.</p>
<pre><code class="language-csharp">LLamaToken SampleTokenMirostat(SafeLLamaContextHandle context, float tau, float eta, int m, Single&amp; mu)
</code></pre>
<h4 id="parameters_15">Parameters</h4>
<p><code>context</code> <a href="../llama.native.safellamacontexthandle/">SafeLLamaContextHandle</a><br></p>
<p><code>tau</code> <a href="https://docs.microsoft.com/en-us/dotnet/api/system.single">Single</a><br>
The target cross-entropy (or surprise) value you want to achieve for the generated text. A higher value corresponds to more surprising or less predictable text, while a lower value corresponds to less surprising or more predictable text.</p>
<p><code>eta</code> <a href="https://docs.microsoft.com/en-us/dotnet/api/system.single">Single</a><br>
The learning rate used to update <code>mu</code> based on the error between the target and observed surprisal of the sampled word. A larger learning rate will cause <code>mu</code> to be updated more quickly, while a smaller learning rate will result in slower updates.</p>
<p><code>m</code> <a href="https://docs.microsoft.com/en-us/dotnet/api/system.int32">Int32</a><br>
The number of tokens considered in the estimation of <code>s_hat</code>. This is an arbitrary value that is used to calculate <code>s_hat</code>, which in turn helps to calculate the value of <code>k</code>. In the paper, they use <code>m = 100</code>, but you can experiment with different values to see how it affects the performance of the algorithm.</p>
<p><code>mu</code> <a href="https://docs.microsoft.com/en-us/dotnet/api/system.single&amp;">Single&amp;</a><br>
Maximum cross-entropy. This value is initialized to be twice the target cross-entropy (<code>2 * tau</code>) and is updated in the algorithm based on the error between the target and observed surprisal.</p>
<h4 id="returns_3">Returns</h4>
<p><a href="../llama.native.llamatoken/">LLamaToken</a><br></p>
<h3 id="sampletokenmirostat2safellamacontexthandle-single-single-single"><strong>SampleTokenMirostat2(SafeLLamaContextHandle, Single, Single, Single&amp;)</strong></h3>
<p>Mirostat 2.0 algorithm described in the paper https://arxiv.org/abs/2007.14966. Uses tokens instead of words.</p>
<pre><code class="language-csharp">LLamaToken SampleTokenMirostat2(SafeLLamaContextHandle context, float tau, float eta, Single&amp; mu)
</code></pre>
<h4 id="parameters_16">Parameters</h4>
<p><code>context</code> <a href="../llama.native.safellamacontexthandle/">SafeLLamaContextHandle</a><br></p>
<p><code>tau</code> <a href="https://docs.microsoft.com/en-us/dotnet/api/system.single">Single</a><br>
The target cross-entropy (or surprise) value you want to achieve for the generated text. A higher value corresponds to more surprising or less predictable text, while a lower value corresponds to less surprising or more predictable text.</p>
<p><code>eta</code> <a href="https://docs.microsoft.com/en-us/dotnet/api/system.single">Single</a><br>
The learning rate used to update <code>mu</code> based on the error between the target and observed surprisal of the sampled word. A larger learning rate will cause <code>mu</code> to be updated more quickly, while a smaller learning rate will result in slower updates.</p>
<p><code>mu</code> <a href="https://docs.microsoft.com/en-us/dotnet/api/system.single&amp;">Single&amp;</a><br>
Maximum cross-entropy. This value is initialized to be twice the target cross-entropy (<code>2 * tau</code>) and is updated in the algorithm based on the error between the target and observed surprisal.</p>
<h4 id="returns_4">Returns</h4>
<p><a href="../llama.native.llamatoken/">LLamaToken</a><br></p>


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