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@@ -8,7 +8,7 @@
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="viewport" content="width=device-width, initial-scale=1" />
<title>mlx.nn.Embedding &#8212; MLX 0.28.0 documentation</title>
<title>mlx.nn.Embedding &#8212; MLX 0.29.0 documentation</title>
@@ -30,15 +30,18 @@
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<script>DOCUMENTATION_OPTIONS.pagename = 'python/nn/_autosummary/mlx.nn.Embedding';</script>
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@@ -137,8 +140,8 @@
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<script>document.write(`<img src="../../../_static/mlx_logo_dark.png" class="logo__image only-dark" alt="MLX 0.28.0 documentation - Home"/>`);</script>
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@@ -477,6 +480,7 @@
<li class="toctree-l2"><a class="reference internal" href="../../_autosummary/mlx.core.fast.rope.html">mlx.core.fast.rope</a></li>
<li class="toctree-l2"><a class="reference internal" href="../../_autosummary/mlx.core.fast.scaled_dot_product_attention.html">mlx.core.fast.scaled_dot_product_attention</a></li>
<li class="toctree-l2"><a class="reference internal" href="../../_autosummary/mlx.core.fast.metal_kernel.html">mlx.core.fast.metal_kernel</a></li>
<li class="toctree-l2"><a class="reference internal" href="../../_autosummary/mlx.core.fast.cuda_kernel.html">mlx.core.fast.cuda_kernel</a></li>
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@@ -523,6 +527,10 @@
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<li class="toctree-l2"><a class="reference internal" href="../../_autosummary/mlx.core.get_active_memory.html">mlx.core.get_active_memory</a></li>
<li class="toctree-l2"><a class="reference internal" href="../../_autosummary/mlx.core.get_peak_memory.html">mlx.core.get_peak_memory</a></li>
@@ -941,7 +949,7 @@ Usually called the vocabulary size.</p></li>
<tr class="row-odd"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">as_linear</span></code>(x)</p></td>
<td><p>Call the embedding layer as a linear layer.</p></td>
</tr>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">to_quantized</span></code>([group_size, bits])</p></td>
<tr class="row-even"><td><p><code class="xref py py-obj docutils literal notranslate"><span class="pre">to_quantized</span></code>([group_size, bits, mode])</p></td>
<td><p>Return a <a class="reference internal" href="mlx.nn.QuantizedEmbedding.html#mlx.nn.QuantizedEmbedding" title="mlx.nn.QuantizedEmbedding"><code class="xref py py-obj docutils literal notranslate"><span class="pre">QuantizedEmbedding</span></code></a> layer that approximates this embedding layer.</p></td>
</tr>
</tbody>