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<a class="posts-list-item-title" href="/posts/finetune-llm-using-pytorch/">Finetune LLM Using Pytorch</a>
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<a class="posts-list-item-title" href="/posts/finetune-llm-locally-using-mlx/">Finetune LLM Locally Using MLX</a>
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‎index.xml

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<description>Recent content on davidgao7 blog</description>
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<lastBuildDate>Sat, 19 Apr 2025 16:59:26 -0400</lastBuildDate>
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<title>Finetune LLM Using Pytorch</title>
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<description>&lt;div class=&#34;highlight&#34;&gt;&lt;pre tabindex=&#34;0&#34; style=&#34;color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;&#34;&gt;&lt;code class=&#34;language-python&#34; data-lang=&#34;python&#34;&gt;&lt;span style=&#34;display:flex;&#34;&gt;&lt;span&gt;&lt;span style=&#34;color:#75715e&#34;&gt;# get datasets, incidently install dependencies to fine tune models from mit&lt;/span&gt;&#xA;&lt;/span&gt;&lt;/span&gt;&lt;span style=&#34;display:flex;&#34;&gt;&lt;span&gt;&lt;span style=&#34;color:#960050;background-color:#1e0010&#34;&gt;!&lt;/span&gt;pip install mitdeeplearning &lt;span style=&#34;color:#75715e&#34;&gt;# &amp;gt; /dev/null 2&amp;gt;&amp;amp;1&lt;/span&gt;&#xA;&lt;/span&gt;&lt;/span&gt;&lt;span style=&#34;display:flex;&#34;&gt;&lt;span&gt;&lt;span style=&#34;color:#f92672&#34;&gt;import&lt;/span&gt; mitdeeplearning &lt;span style=&#34;color:#66d9ef&#34;&gt;as&lt;/span&gt; mdl&#xA;&lt;/span&gt;&lt;/span&gt;&lt;/code&gt;&lt;/pre&gt;&lt;/div&gt;&lt;pre&gt;&lt;code&gt;[0mSuccessfully installed boto3-stubs-1.38.0 botocore-stubs-1.38.0 datasets-3.5.0 dill-0.3.8 fsspec-2024.12.0 levenshtein-0.27.1 lion-pytorch-0.2.3 litellm-1.67.1 mitdeeplearning-0.7.5 multiprocess-0.70.16 mypy-boto3-bedrock-runtime-1.38.0 nvidia-cublas-cu12-12.4.5.8 nvidia-cuda-cupti-cu12-12.4.127 nvidia-cuda-nvrtc-cu12-12.4.127 nvidia-cuda-runtime-cu12-12.4.127 nvidia-cudnn-cu12-9.1.0.70 nvidia-cufft-cu12-11.2.1.3 nvidia-curand-cu12-10.3.5.147 nvidia-cusolver-cu12-11.6.1.9 nvidia-cusparse-cu12-12.3.1.170 nvidia-nvjitlink-cu12-12.4.127 opik-1.7.9 pydantic-settings-2.9.1 python-dotenv-1.1.0 rapidfuzz-3.13.0 tiktoken-0.9.0 types-awscrt-0.26.1 types-s3transfer-0.11.5 uuid6-2024.7.10 xxhash-3.5.0&#xA;&lt;/code&gt;&lt;/pre&gt;&#xA;&lt;div class=&#34;highlight&#34;&gt;&lt;pre tabindex=&#34;0&#34; style=&#34;color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;&#34;&gt;&lt;code class=&#34;language-python&#34; data-lang=&#34;python&#34;&gt;&lt;span style=&#34;display:flex;&#34;&gt;&lt;span&gt;&lt;span style=&#34;color:#f92672&#34;&gt;import&lt;/span&gt; os&#xA;&lt;/span&gt;&lt;/span&gt;&lt;span style=&#34;display:flex;&#34;&gt;&lt;span&gt;&lt;span style=&#34;color:#f92672&#34;&gt;import&lt;/span&gt; json&#xA;&lt;/span&gt;&lt;/span&gt;&lt;span style=&#34;display:flex;&#34;&gt;&lt;span&gt;&lt;span style=&#34;color:#f92672&#34;&gt;import&lt;/span&gt; numpy &lt;span style=&#34;color:#66d9ef&#34;&gt;as&lt;/span&gt; np&#xA;&lt;/span&gt;&lt;/span&gt;&lt;span style=&#34;display:flex;&#34;&gt;&lt;span&gt;&lt;span style=&#34;color:#f92672&#34;&gt;from&lt;/span&gt; tqdm &lt;span style=&#34;color:#f92672&#34;&gt;import&lt;/span&gt; tqdm&#xA;&lt;/span&gt;&lt;/span&gt;&lt;span style=&#34;display:flex;&#34;&gt;&lt;span&gt;&lt;span style=&#34;color:#f92672&#34;&gt;import&lt;/span&gt; matplotlib.pyplot &lt;span style=&#34;color:#66d9ef&#34;&gt;as&lt;/span&gt; plt&#xA;&lt;/span&gt;&lt;/span&gt;&lt;span style=&#34;display:flex;&#34;&gt;&lt;span&gt;&#xA;&lt;/span&gt;&lt;/span&gt;&lt;span style=&#34;display:flex;&#34;&gt;&lt;span&gt;&lt;span style=&#34;color:#f92672&#34;&gt;import&lt;/span&gt; torch&#xA;&lt;/span&gt;&lt;/span&gt;&lt;span style=&#34;display:flex;&#34;&gt;&lt;span&gt;&lt;span style=&#34;color:#f92672&#34;&gt;from&lt;/span&gt; torch.nn &lt;span style=&#34;color:#f92672&#34;&gt;import&lt;/span&gt; functional &lt;span style=&#34;color:#66d9ef&#34;&gt;as&lt;/span&gt; F&#xA;&lt;/span&gt;&lt;/span&gt;&lt;span style=&#34;display:flex;&#34;&gt;&lt;span&gt;&lt;span style=&#34;color:#f92672&#34;&gt;from&lt;/span&gt; torch.utils.data &lt;span style=&#34;color:#f92672&#34;&gt;import&lt;/span&gt; DataLoader&#xA;&lt;/span&gt;&lt;/span&gt;&lt;span style=&#34;display:flex;&#34;&gt;&lt;span&gt;&#xA;&lt;/span&gt;&lt;/span&gt;&lt;span style=&#34;display:flex;&#34;&gt;&lt;span&gt;&lt;span style=&#34;color:#f92672&#34;&gt;from&lt;/span&gt; transformers &lt;span style=&#34;color:#f92672&#34;&gt;import&lt;/span&gt; AutoTokenizer, AutoModelForCausalLM&#xA;&lt;/span&gt;&lt;/span&gt;&lt;span style=&#34;display:flex;&#34;&gt;&lt;span&gt;&lt;span style=&#34;color:#f92672&#34;&gt;from&lt;/span&gt; datasets &lt;span style=&#34;color:#f92672&#34;&gt;import&lt;/span&gt; load_dataset&#xA;&lt;/span&gt;&lt;/span&gt;&lt;span style=&#34;display:flex;&#34;&gt;&lt;span&gt;&lt;span style=&#34;color:#f92672&#34;&gt;from&lt;/span&gt; peft &lt;span style=&#34;color:#f92672&#34;&gt;import&lt;/span&gt; LoraConfig, get_peft_model&#xA;&lt;/span&gt;&lt;/span&gt;&lt;span style=&#34;display:flex;&#34;&gt;&lt;span&gt;&lt;span style=&#34;color:#f92672&#34;&gt;from&lt;/span&gt; lion_pytorch &lt;span style=&#34;color:#f92672&#34;&gt;import&lt;/span&gt; Lion&#xA;&lt;/span&gt;&lt;/span&gt;&lt;/code&gt;&lt;/pre&gt;&lt;/div&gt;&lt;h1 id=&#34;fine-tuning-gemma-2b-as-a-chatbot&#34;&gt;Fine tuning Gemma 2B as a chatbot&lt;/h1&gt;&#xA;&lt;h2 id=&#34;templating-and-tokenization&#34;&gt;Templating and tokenization&lt;/h2&gt;&#xA;&lt;h3 id=&#34;templating&#34;&gt;Templating&lt;/h3&gt;&#xA;&lt;p&gt;Language models that function as chatbots are able to generate responses to user questies &amp;ndash; but how do they do this?&lt;/p&gt;</description>
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<title>VLLM Deep Dive</title>
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<pubDate>Tue, 22 Apr 2025 11:14:45 -0400</pubDate>
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<description>&lt;h1 id=&#34;how-to-apply-llm-in-production&#34;&gt;How to apply LLM in production&lt;/h1&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Introducing project vLLM&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;h2 id=&#34;what-is-vllm&#34;&gt;What is vLLM?&lt;/h2&gt;&#xA;&lt;ul&gt;&#xA;&lt;li&gt;&lt;strong&gt;vLLM is a fast and easy-to-use library for &lt;font color=pink&gt;LLM inference&lt;/font&gt; and &lt;font color=pink&gt;serving&lt;/font&gt;.&lt;/strong&gt;&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;p&gt;Longer version&amp;hellip;&lt;/p&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;vLLM is a high-performance, memory-efficient, and easy-to-use library for serving large language models (LLMs) in production. It is designed to optimize the inference of LLMs, making it easier to deploy and scale them in real-world applications.&lt;/p&gt;&lt;/blockquote&gt;&#xA;&lt;blockquote&gt;&#xA;&lt;p&gt;“vLLM is to LLM serving what TensorRT was to DL inference: high performance, low frills, and production first.”&lt;/p&gt;</description>
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<description>&lt;p&gt;%% Zoottelkeeper: Beginning of the autogenerated index file list %%&#xA;[[davidgao7blogs/content/posts/array-summary|array-summary]]&#xA;[[davidgao7blogs/content/posts/binary-tree-path-sum|binary-tree-path-sum]]&#xA;[[davidgao7blogs/content/posts/binaryTree-Output-levely|binaryTree-Output-levely]]&#xA;[[davidgao7blogs/content/posts/copy-random-list|copy-random-list]]&#xA;[[davidgao7blogs/content/posts/cout-vowel-strings|cout-vowel-strings]]&#xA;[[davidgao7blogs/content/posts/divide-arr-into-arr-with-max-diff|divide-arr-into-arr-with-max-diff]]&#xA;[[davidgao7blogs/content/posts/evolution-of-route-planning-in-urban-env|evolution-of-route-planning-in-urban-env]]&#xA;[[davidgao7blogs/content/posts/find-kth-largest|find-kth-largest]]&#xA;[[davidgao7blogs/content/posts/Finetune-LLM-Locally-using-MLX|Finetune-LLM-Locally-using-MLX]]&#xA;[[davidgao7blogs/content/posts/go-syntax-learning|go-syntax-learning]]&#xA;[[davidgao7blogs/content/posts/grafana-prometheus|grafana-prometheus]]&#xA;[[davidgao7blogs/content/posts/heap-bst|heap-bst]]&#xA;[[davidgao7blogs/content/posts/how-to-build-n8n-agent-from-scratch|how-to-build-n8n-agent-from-scratch]]&#xA;[[davidgao7blogs/content/posts/jump-game|jump-game]]&#xA;[[davidgao7blogs/content/posts/LLM-Production|LLM-Production]]&#xA;[[davidgao7blogs/content/posts/local-rag-ollama|local-rag-ollama]]&#xA;[[davidgao7blogs/content/posts/lowest-common-ancestor|lowest-common-ancestor]]&#xA;[[davidgao7blogs/content/posts/machine-learning-pipeline|machine-learning-pipeline]]&#xA;[[davidgao7blogs/content/posts/maxLength|maxLength]]&#xA;[[davidgao7blogs/content/posts/merge-k-sorted-lists|merge-k-sorted-lists]]&#xA;[[davidgao7blogs/content/posts/minimum-length-encoding|minimum-length-encoding]]&#xA;[[davidgao7blogs/content/posts/rob|rob]]&#xA;[[davidgao7blogs/content/posts/shortest-bridge|shortest-bridge]]&#xA;[[davidgao7blogs/content/posts/SVM|SVM]]&#xA;[[davidgao7blogs/content/posts/symmetric-tree|symmetric-tree]]&#xA;[[davidgao7blogs/content/posts/TCP-rust|TCP-rust]]&#xA;[[davidgao7blogs/content/posts/valid-word-abbr|valid-word-abbr]]&#xA;[[davidgao7blogs/content/posts/virtual-machine|virtual-machine]]&#xA;%% Zoottelkeeper: End of the autogenerated index file list %%&lt;/p&gt;</description>
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<description>&lt;p&gt;%% Zoottelkeeper: Beginning of the autogenerated index file list %%&#xA;[[davidgao7blogs/content/posts/array-summary|array-summary]]&#xA;[[davidgao7blogs/content/posts/binary-tree-path-sum|binary-tree-path-sum]]&#xA;[[davidgao7blogs/content/posts/binaryTree-Output-levely|binaryTree-Output-levely]]&#xA;[[davidgao7blogs/content/posts/copy-random-list|copy-random-list]]&#xA;[[davidgao7blogs/content/posts/cout-vowel-strings|cout-vowel-strings]]&#xA;[[davidgao7blogs/content/posts/divide-arr-into-arr-with-max-diff|divide-arr-into-arr-with-max-diff]]&#xA;[[davidgao7blogs/content/posts/evolution-of-route-planning-in-urban-env|evolution-of-route-planning-in-urban-env]]&#xA;[[davidgao7blogs/content/posts/find-kth-largest|find-kth-largest]]&#xA;[[davidgao7blogs/content/posts/Finetune-LLM-Locally-using-MLX|Finetune-LLM-Locally-using-MLX]]&#xA;[[davidgao7blogs/content/posts/Finetune-LLM-using-pytorch|Finetune-LLM-using-pytorch]]&#xA;[[davidgao7blogs/content/posts/go-syntax-learning|go-syntax-learning]]&#xA;[[davidgao7blogs/content/posts/grafana-prometheus|grafana-prometheus]]&#xA;[[davidgao7blogs/content/posts/heap-bst|heap-bst]]&#xA;[[davidgao7blogs/content/posts/how-to-build-n8n-agent-from-scratch|how-to-build-n8n-agent-from-scratch]]&#xA;[[davidgao7blogs/content/posts/jump-game|jump-game]]&#xA;[[davidgao7blogs/content/posts/LLM-Production|LLM-Production]]&#xA;[[davidgao7blogs/content/posts/local-rag-ollama|local-rag-ollama]]&#xA;[[davidgao7blogs/content/posts/lowest-common-ancestor|lowest-common-ancestor]]&#xA;[[davidgao7blogs/content/posts/machine-learning-pipeline|machine-learning-pipeline]]&#xA;[[davidgao7blogs/content/posts/maxLength|maxLength]]&#xA;[[davidgao7blogs/content/posts/merge-k-sorted-lists|merge-k-sorted-lists]]&#xA;[[davidgao7blogs/content/posts/minimum-length-encoding|minimum-length-encoding]]&#xA;[[davidgao7blogs/content/posts/rob|rob]]&#xA;[[davidgao7blogs/content/posts/shortest-bridge|shortest-bridge]]&#xA;[[davidgao7blogs/content/posts/SVM|SVM]]&#xA;[[davidgao7blogs/content/posts/symmetric-tree|symmetric-tree]]&#xA;[[davidgao7blogs/content/posts/TCP-rust|TCP-rust]]&#xA;[[davidgao7blogs/content/posts/valid-word-abbr|valid-word-abbr]]&#xA;[[davidgao7blogs/content/posts/virtual-machine|virtual-machine]]&#xA;[[davidgao7blogs/content/posts/vLLM-deep-dive|vLLM-deep-dive]]&#xA;%% Zoottelkeeper: End of the autogenerated index file list %%&lt;/p&gt;</description>
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