Fixing default names for Phi2 and MistralAI (#14338)

* Fixing default names for Phi2 and MistralAI

* Phi2 is 2.7B in size

---------

Co-authored-by: Maziyar Panahi <maziyar.panahi@iscpif.fr>

docs/api/com/johnsnowlabs/nlp/annotators/seq2seq/MistralTransformer.html

@@ -286,9 +286,9 @@ <h4 id="signature" class="signature">
 process extensive textual input, expanding its utility in handling more complex tasks.</p><p>In summary, Mistral 7B represents a notable advancement in language models, offering a
 reliable and versatile solution for various natural language processing challenges.</p><p>Pretrained models can be loaded with <code>pretrained</code> of the companion object:</p><pre><span class="kw">val</span> mistral = MistralTransformer.pretrained()
   .setInputCols(<span class="lit">"document"</span>)
-  .setOutputCol(<span class="lit">"generation"</span>)</pre><p>The default model is <code>&quot;mistral-7b&quot;</code>, if no name is provided. For available pretrained models
+  .setOutputCol(<span class="lit">"generation"</span>)</pre><p>The default model is <code>&quot;mistral_7b&quot;</code>, if no name is provided. For available pretrained models
 please see the <a href="https://sparknlp.org/models?q=mistral" target="_blank">Models Hub</a>.</p><p>For extended examples of usage, see
-<a href="https://github.com/JohnSnowLabs/spark-nlp/blob/master/src/test/scala/com/johnsnowlabs/nlp/annotators/seq2seq/MistralTestSpec.scala" target="_blank">MistralTestSpec</a>.</p><p><b>References:</b></p><ul><li><a href="https://mistral.ai/news/announcing-mistral-7b/" target="_blank">Mistral 7B</a></li><li><a href="https://github.com/mistralai/mistral-src" target="_blank">https://github.com/mistralai/mistral-src</a></li></ul><p><b>Paper Abstract:</b></p><p><i>We introduce Mistral 7B v0.1, a 7-billion-parameter language model engineered for superior
+<a href="https://github.com/JohnSnowLabs/spark-nlp/blob/master/src/test/scala/com/johnsnowlabs/nlp/annotators/seq2seq/MistralTestSpec.scala" target="_blank">MistralTestSpec</a>.</p><p><b>References:</b></p><ul><li><a href="https://mistral.ai/news/announcing-mistral_7b/" target="_blank">Mistral 7B</a></li><li><a href="https://github.com/mistralai/mistral-src" target="_blank">https://github.com/mistralai/mistral-src</a></li></ul><p><b>Paper Abstract:</b></p><p><i>We introduce Mistral 7B v0.1, a 7-billion-parameter language model engineered for superior
 performance and efficiency. Mistral 7B outperforms Llama 2 13B across all evaluated
 benchmarks, and Llama 1 34B in reasoning, mathematics, and code generation. Our model
 leverages grouped-query attention (GQA) for faster inference, coupled with sliding window
@@ -305,7 +305,7 @@ <h4 id="signature" class="signature">
   .setInputCol(<span class="lit">"text"</span>)
   .setOutputCol(<span class="lit">"documents"</span>)
 
-<span class="kw">val</span> mistral = MistralTransformer.pretrained(<span class="lit">"mistral-7b"</span>)
+<span class="kw">val</span> mistral = MistralTransformer.pretrained(<span class="lit">"mistral_7b"</span>)
   .setInputCols(<span class="std">Array</span>(<span class="lit">"documents"</span>))
   .setMinOutputLength(<span class="num">10</span>)
   .setMaxOutputLength(<span class="num">50</span>)

docs/api/com/johnsnowlabs/nlp/annotators/seq2seq/Phi2Transformer.html

@@ -311,7 +311,7 @@ <h4 id="signature" class="signature">
   .setInputCol(<span class="lit">"text"</span>)
   .setOutputCol(<span class="lit">"documents"</span>)
 
-<span class="kw">val</span> Phi2 = Phi2Transformer.pretrained(<span class="lit">"Phi2-7b"</span>)
+<span class="kw">val</span> Phi2 = Phi2Transformer.pretrained(<span class="lit">"phi2_7b"</span>)
   .setInputCols(<span class="std">Array</span>(<span class="lit">"documents"</span>))
   .setMinOutputLength(<span class="num">10</span>)
   .setMaxOutputLength(<span class="num">50</span>)

docs/api/com/johnsnowlabs/nlp/annotators/seq2seq/index.html

@@ -1040,9 +1040,9 @@ <h3>Type Members</h3>
 process extensive textual input, expanding its utility in handling more complex tasks.</p><p>In summary, Mistral 7B represents a notable advancement in language models, offering a
 reliable and versatile solution for various natural language processing challenges.</p><p>Pretrained models can be loaded with <code>pretrained</code> of the companion object:</p><pre><span class="kw">val</span> mistral = MistralTransformer.pretrained()
   .setInputCols(<span class="lit">"document"</span>)
-  .setOutputCol(<span class="lit">"generation"</span>)</pre><p>The default model is <code>&quot;mistral-7b&quot;</code>, if no name is provided. For available pretrained models
+  .setOutputCol(<span class="lit">"generation"</span>)</pre><p>The default model is <code>&quot;mistral_7b&quot;</code>, if no name is provided. For available pretrained models
 please see the <a href="https://sparknlp.org/models?q=mistral" target="_blank">Models Hub</a>.</p><p>For extended examples of usage, see
-<a href="https://github.com/JohnSnowLabs/spark-nlp/blob/master/src/test/scala/com/johnsnowlabs/nlp/annotators/seq2seq/MistralTestSpec.scala" target="_blank">MistralTestSpec</a>.</p><p><b>References:</b></p><ul><li><a href="https://mistral.ai/news/announcing-mistral-7b/" target="_blank">Mistral 7B</a></li><li><a href="https://github.com/mistralai/mistral-src" target="_blank">https://github.com/mistralai/mistral-src</a></li></ul><p><b>Paper Abstract:</b></p><p><i>We introduce Mistral 7B v0.1, a 7-billion-parameter language model engineered for superior
+<a href="https://github.com/JohnSnowLabs/spark-nlp/blob/master/src/test/scala/com/johnsnowlabs/nlp/annotators/seq2seq/MistralTestSpec.scala" target="_blank">MistralTestSpec</a>.</p><p><b>References:</b></p><ul><li><a href="https://mistral.ai/news/announcing-mistral_7b/" target="_blank">Mistral 7B</a></li><li><a href="https://github.com/mistralai/mistral-src" target="_blank">https://github.com/mistralai/mistral-src</a></li></ul><p><b>Paper Abstract:</b></p><p><i>We introduce Mistral 7B v0.1, a 7-billion-parameter language model engineered for superior
 performance and efficiency. Mistral 7B outperforms Llama 2 13B across all evaluated
 benchmarks, and Llama 1 34B in reasoning, mathematics, and code generation. Our model
 leverages grouped-query attention (GQA) for faster inference, coupled with sliding window
@@ -1059,7 +1059,7 @@ <h3>Type Members</h3>
   .setInputCol(<span class="lit">"text"</span>)
   .setOutputCol(<span class="lit">"documents"</span>)
 
-<span class="kw">val</span> mistral = MistralTransformer.pretrained(<span class="lit">"mistral-7b"</span>)
+<span class="kw">val</span> mistral = MistralTransformer.pretrained(<span class="lit">"mistral_7b"</span>)
   .setInputCols(<span class="std">Array</span>(<span class="lit">"documents"</span>))
   .setMinOutputLength(<span class="num">10</span>)
   .setMaxOutputLength(<span class="num">50</span>)
@@ -1134,7 +1134,7 @@ <h3>Type Members</h3>
   .setInputCol(<span class="lit">"text"</span>)
   .setOutputCol(<span class="lit">"documents"</span>)
 
-<span class="kw">val</span> Phi2 = Phi2Transformer.pretrained(<span class="lit">"Phi2-7b"</span>)
+<span class="kw">val</span> Phi2 = Phi2Transformer.pretrained(<span class="lit">"phi2_7b"</span>)
   .setInputCols(<span class="std">Array</span>(<span class="lit">"documents"</span>))
   .setMinOutputLength(<span class="num">10</span>)
   .setMaxOutputLength(<span class="num">50</span>)

docs/api/python/modules/sparknlp/annotator/seq2seq/mistral_transformer.html

@@ -387,7 +387,7 @@ <h1>Source code for sparknlp.annotator.seq2seq.mistral_transformer</h1><div clas
 <span class="sd">    ...     .setOutputCol(&quot;generation&quot;)</span>
 
 
-<span class="sd">    The default model is ``&quot;mistral-7b&quot;``, if no name is provided. For available</span>
+<span class="sd">    The default model is ``&quot;mistral_7b&quot;``, if no name is provided. For available</span>
 <span class="sd">    pretrained models please see the `Models Hub</span>
 <span class="sd">    &lt;https://sparknlp.org/models?q=mistral&gt;`__.</span>
 
@@ -435,7 +435,7 @@ <h1>Source code for sparknlp.annotator.seq2seq.mistral_transformer</h1><div clas
 <span class="sd">    References</span>
 <span class="sd">    ----------</span>
 <span class="sd">    - `Mistral 7B</span>
-<span class="sd">      &lt;https://mistral.ai/news/announcing-mistral-7b/&gt;`__</span>
+<span class="sd">      &lt;https://mistral.ai/news/announcing-mistral_7b/&gt;`__</span>
 <span class="sd">    - https://github.com/mistralai/mistral-src</span>
 
 <span class="sd">    **Paper Abstract:**</span>
@@ -458,7 +458,7 @@ <h1>Source code for sparknlp.annotator.seq2seq.mistral_transformer</h1><div clas
 <span class="sd">    &gt;&gt;&gt; documentAssembler = DocumentAssembler() \\</span>
 <span class="sd">    ...     .setInputCol(&quot;text&quot;) \\</span>
 <span class="sd">    ...     .setOutputCol(&quot;documents&quot;)</span>
-<span class="sd">    &gt;&gt;&gt; mistral = MistralTransformer.pretrained(&quot;mistral-7b&quot;) \\</span>
+<span class="sd">    &gt;&gt;&gt; mistral = MistralTransformer.pretrained(&quot;mistral_7b&quot;) \\</span>
 <span class="sd">    ...     .setInputCols([&quot;documents&quot;]) \\</span>
 <span class="sd">    ...     .setMaxOutputLength(50) \\</span>
 <span class="sd">    ...     .setOutputCol(&quot;generation&quot;)</span>
@@ -670,13 +670,13 @@ <h1>Source code for sparknlp.annotator.seq2seq.mistral_transformer</h1><div clas
         <span class="k">return</span> <span class="n">MistralTransformer</span><span class="p">(</span><span class="n">java_model</span><span class="o">=</span><span class="n">jModel</span><span class="p">)</span></div>
 
     <span class="nd">@staticmethod</span>
-<div class="viewcode-block" id="MistralTransformer.pretrained"><a class="viewcode-back" href="../../../../reference/autosummary/sparknlp/annotator/seq2seq/mistral_transformer/index.html#sparknlp.annotator.seq2seq.mistral_transformer.MistralTransformer.pretrained">[docs]</a>    <span class="k">def</span> <span class="nf">pretrained</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;mistral-7b&quot;</span><span class="p">,</span> <span class="n">lang</span><span class="o">=</span><span class="s2">&quot;en&quot;</span><span class="p">,</span> <span class="n">remote_loc</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
+<div class="viewcode-block" id="MistralTransformer.pretrained"><a class="viewcode-back" href="../../../../reference/autosummary/sparknlp/annotator/seq2seq/mistral_transformer/index.html#sparknlp.annotator.seq2seq.mistral_transformer.MistralTransformer.pretrained">[docs]</a>    <span class="k">def</span> <span class="nf">pretrained</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;mistral_7b&quot;</span><span class="p">,</span> <span class="n">lang</span><span class="o">=</span><span class="s2">&quot;en&quot;</span><span class="p">,</span> <span class="n">remote_loc</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
 <span class="w">        </span><span class="sd">&quot;&quot;&quot;Downloads and loads a pretrained model.</span>
 
 <span class="sd">        Parameters</span>
 <span class="sd">        ----------</span>
 <span class="sd">        name : str, optional</span>
-<span class="sd">            Name of the pretrained model, by default &quot;mistral-7b&quot;</span>
+<span class="sd">            Name of the pretrained model, by default &quot;mistral_7b&quot;</span>
 <span class="sd">        lang : str, optional</span>
 <span class="sd">            Language of the pretrained model, by default &quot;en&quot;</span>
 <span class="sd">        remote_loc : str, optional</span>

docs/api/python/modules/sparknlp/annotator/seq2seq/phi2_transformer.html

@@ -451,7 +451,7 @@ <h1>Source code for sparknlp.annotator.seq2seq.phi2_transformer</h1><div class="
 <span class="sd">    &gt;&gt;&gt; documentAssembler = DocumentAssembler() \\</span>
 <span class="sd">    ...     .setInputCol(&quot;text&quot;) \\</span>
 <span class="sd">    ...     .setOutputCol(&quot;documents&quot;)</span>
-<span class="sd">    &gt;&gt;&gt; phi2 = Phi2Transformer.pretrained(&quot;phi2-7b&quot;) \\</span>
+<span class="sd">    &gt;&gt;&gt; phi2 = Phi2Transformer.pretrained(&quot;phi2_7b&quot;) \\</span>
 <span class="sd">    ...     .setInputCols([&quot;documents&quot;]) \\</span>
 <span class="sd">    ...     .setMaxOutputLength(50) \\</span>
 <span class="sd">    ...     .setOutputCol(&quot;generation&quot;)</span>
@@ -647,13 +647,13 @@ <h1>Source code for sparknlp.annotator.seq2seq.phi2_transformer</h1><div class="
         <span class="k">return</span> <span class="n">Phi2Transformer</span><span class="p">(</span><span class="n">java_model</span><span class="o">=</span><span class="n">jModel</span><span class="p">)</span></div>
 
     <span class="nd">@staticmethod</span>
-<div class="viewcode-block" id="Phi2Transformer.pretrained"><a class="viewcode-back" href="../../../../reference/autosummary/sparknlp/annotator/seq2seq/phi2_transformer/index.html#sparknlp.annotator.seq2seq.phi2_transformer.Phi2Transformer.pretrained">[docs]</a>    <span class="k">def</span> <span class="nf">pretrained</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;phi2-7b&quot;</span><span class="p">,</span> <span class="n">lang</span><span class="o">=</span><span class="s2">&quot;en&quot;</span><span class="p">,</span> <span class="n">remote_loc</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
+<div class="viewcode-block" id="Phi2Transformer.pretrained"><a class="viewcode-back" href="../../../../reference/autosummary/sparknlp/annotator/seq2seq/phi2_transformer/index.html#sparknlp.annotator.seq2seq.phi2_transformer.Phi2Transformer.pretrained">[docs]</a>    <span class="k">def</span> <span class="nf">pretrained</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;phi2_7b&quot;</span><span class="p">,</span> <span class="n">lang</span><span class="o">=</span><span class="s2">&quot;en&quot;</span><span class="p">,</span> <span class="n">remote_loc</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
 <span class="w">        </span><span class="sd">&quot;&quot;&quot;Downloads and loads a pretrained model.</span>
 
 <span class="sd">        Parameters</span>
 <span class="sd">        ----------</span>
 <span class="sd">        name : str, optional</span>
-<span class="sd">            Name of the pretrained model, by default &quot;phi2-7b&quot;</span>
+<span class="sd">            Name of the pretrained model, by default &quot;phi2_7b&quot;</span>
 <span class="sd">        lang : str, optional</span>
 <span class="sd">            Language of the pretrained model, by default &quot;en&quot;</span>
 <span class="sd">        remote_loc : str, optional</span>

docs/api/python/reference/autosummary/sparknlp/annotator/seq2seq/mistral_transformer/index.html

@@ -543,7 +543,7 @@ <h3>Classes<a class="headerlink" href="#classes" title="Permalink to this headin
 <span class="gp">... </span>    <span class="o">.</span><span class="n">setOutputCol</span><span class="p">(</span><span class="s2">&quot;generation&quot;</span><span class="p">)</span>
 </pre></div>
 </div>
-<p>The default model is <code class="docutils literal notranslate"><span class="pre">&quot;mistral-7b&quot;</span></code>, if no name is provided. For available
+<p>The default model is <code class="docutils literal notranslate"><span class="pre">&quot;mistral_7b&quot;</span></code>, if no name is provided. For available
 pretrained models please see the <a class="reference external" href="https://sparknlp.org/models?q=mistral">Models Hub</a>.</p>
 <table class="table">
 <thead>
@@ -772,12 +772,12 @@ <h3>Classes<a class="headerlink" href="#classes" title="Permalink to this headin
 
 <dl class="py method">
 <dt class="sig sig-object py" id="sparknlp.annotator.seq2seq.mistral_transformer.MistralTransformer.pretrained">
-<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">pretrained</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'mistral-7b'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lang</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'en'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">remote_loc</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../modules/sparknlp/annotator/seq2seq/mistral_transformer.html#MistralTransformer.pretrained"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sparknlp.annotator.seq2seq.mistral_transformer.MistralTransformer.pretrained" title="Permalink to this definition">#</a></dt>
+<em class="property"><span class="pre">static</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">pretrained</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'mistral_7b'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">lang</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'en'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">remote_loc</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../../../../modules/sparknlp/annotator/seq2seq/mistral_transformer.html#MistralTransformer.pretrained"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#sparknlp.annotator.seq2seq.mistral_transformer.MistralTransformer.pretrained" title="Permalink to this definition">#</a></dt>
 <dd><p>Downloads and loads a pretrained model.</p>
 <dl class="field-list simple">
 <dt class="field-odd">Parameters<span class="colon">:</span></dt>
 <dd class="field-odd"><dl class="simple">
-<dt><strong>name</strong><span class="classifier">str, optional</span></dt><dd><p>Name of the pretrained model, by default “mistral-7b”</p>
+<dt><strong>name</strong><span class="classifier">str, optional</span></dt><dd><p>Name of the pretrained model, by default “mistral_7b”</p>
 </dd>
 <dt><strong>lang</strong><span class="classifier">str, optional</span></dt><dd><p>Language of the pretrained model, by default “en”</p>
 </dd>