updated portfolio with static files for text summarizer

Author: GoJo-Rika

blog.html

@@ -89,6 +89,54 @@ <h2 class="section-heading">Recent Posts</h2>
 
                     <!-- blogs -->
 
+                    <article class="blog-post" data-tags="huggingface transformers,pytorch,fastapi,docker,python,weights &amp; biases,mlops,nlp">
+                        <h3 class="post-meta">
+                            <a href="posts/text-summarizer-journey-serving-the-model-part-3.html">Text Summarizer Journey: Serving the Model (Part 3)</a>
+                        </h3>
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+                        <p class="section-label">Published on: 2025-09-18</p>
+                        
+                            <p>The final step in our MLOps journey is making the trained model useful. This post covers the "last mile" of deployment, showing how to wrap the text summarization model in a high-performance API using FastAPI. I then walk through creating a Dockerfile to containerize the entire application, ensuring a consistent and portable service that can be deployed anywhere.</p>
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+                        <div class="tech-stack">
+                            
+                        </div>
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+                    </article>
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+                    <article class="blog-post" data-tags="huggingface transformers,pytorch,fastapi,docker,python,weights &amp; biases,mlops,nlp">
+                        <h3 class="post-meta">
+                            <a href="posts/text-summarizer-journey-the-ml-engine-room-part-2.html">Text Summarizer Journey: The ML Engine Room (Part 2)</a>
+                        </h3>
+                        
+                        <p class="section-label">Published on: 2025-09-17</p>
+                        
+                            <p>With a robust MLOps pipeline in place, this post dives into the core machine learning workflow of the Text Summarizer project. I explore each critical stage: transforming the raw SAMSum dataset for the model, fine-tuning a pre-trained Pegasus Transformer using a configuration-driven approach, and quantitatively evaluating its performance with ROUGE metrics.</p>
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+                        <div class="tech-stack">
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+                        </div>
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+                    </article>
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+                    <article class="blog-post" data-tags="huggingface transformers,pytorch,fastapi,docker,python,weights &amp; biases,mlops,nlp">
+                        <h3 class="post-meta">
+                            <a href="posts/text-summarizer-journey-the-mlops-blueprint-part-1.html">Text Summarizer Journey: The MLOps Blueprint (Part 1)</a>
+                        </h3>
+                        
+                        <p class="section-label">Published on: 2025-09-16</p>
+                        
+                            <p>My Text Summarizer project started in a Jupyter notebook—a great place for experimentation, but a fragile foundation for a real application. This post details the journey of refactoring that initial script into a robust, production-ready MLOps pipeline, tackling the challenges of hardcoded paths, scattered configuration, and monolithic execution with a modular, component-based architecture.</p>
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+                        <div class="tech-stack">
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+                    </article>
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                     <article class="blog-post" data-tags="aws,aws sagemaker,scikit-learn,aws s3,python,mlops,cloudwatch">
                         <h3 class="post-meta">
                             <a href="posts/when-sagemaker-humbled-me-a-cloud-native-ml-reality-check.html">When SageMaker Humbled Me: A Cloud-Native ML Reality Check</a>
@@ -202,12 +250,16 @@ <h2 class="section-heading">Filter by Technology</h2>
 
                         <button class="tag filter-tag" data-tag="github actions">GitHub Actions</button>
 
+                        <button class="tag filter-tag" data-tag="huggingface transformers">HuggingFace Transformers</button>
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                         <button class="tag filter-tag" data-tag="mlops">MLOps</button>
 
                         <button class="tag filter-tag" data-tag="mlflow">MLflow</button>
 
                         <button class="tag filter-tag" data-tag="mongodb">MongoDB</button>
 
+                        <button class="tag filter-tag" data-tag="nlp">NLP</button>
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                         <button class="tag filter-tag" data-tag="pytorch">PyTorch</button>
 
                         <button class="tag filter-tag" data-tag="python">Python</button>
@@ -216,6 +268,8 @@ <h2 class="section-heading">Filter by Technology</h2>
 
                         <button class="tag filter-tag" data-tag="tensorboard">TensorBoard</button>
 
+                        <button class="tag filter-tag" data-tag="weights &amp; biases">Weights &amp; Biases</button>
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                         <button class="tag filter-tag" data-tag="torchvision">torchvision</button>
 
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