MICRO-COURSE

Model Adaptation & Inference Optimization

Model Adaptation & Inference Optimization: 13 short lessons, one for each concept. Fine-tuning, supervised fine-tuning, parameter-efficient fine-tuning, LoRA, preference optimization, reinforcement learning from feedback, distillation, quantization, pruning, batching, KV caching, speculative decodi

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01 / WATCH

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02 / UNDERSTAND

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Fine-tuning, supervised fine-tuning, parameter-efficient fine-tuning, LoRA, preference optimization, reinforcement learning from feedback, distillation, quantization, pruning, batching, KV caching, speculative decoding, and model parallelism.

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Concept scope

03 / TRY IT

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13 results1–12

Lesson

Fine-tuning

A short lesson on fine-tuning from the Model Adaptation & Inference Optimization micro course: what it is, where it shows up in real systems, and a practical example you can apply.

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Lesson

Supervised fine-tuning

A short lesson on supervised fine-tuning from the Model Adaptation & Inference Optimization micro course: what it is, where it shows up in real systems, and a practical example you can apply.

Open lesson

Lesson

Parameter-efficient fine-tuning

A short lesson on parameter-efficient fine-tuning from the Model Adaptation & Inference Optimization micro course: what it is, where it shows up in real systems, and a practical example you can apply.

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Lesson

LoRA

A short lesson on LoRA from the Model Adaptation & Inference Optimization micro course: what it is, where it shows up in real systems, and a practical example you can apply.

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Lesson

Preference optimization

A short lesson on preference optimization from the Model Adaptation & Inference Optimization micro course: what it is, where it shows up in real systems, and a practical example you can apply.

Open lesson

Lesson

Reinforcement learning from feedback

A short lesson on reinforcement learning from feedback from the Model Adaptation & Inference Optimization micro course: what it is, where it shows up in real systems, and a practical example you can apply.

Open lesson

Lesson

Distillation

A short lesson on distillation from the Model Adaptation & Inference Optimization micro course: what it is, where it shows up in real systems, and a practical example you can apply.

Open lesson

Lesson

Quantization

A short lesson on quantization from the Model Adaptation & Inference Optimization micro course: what it is, where it shows up in real systems, and a practical example you can apply.

Open lesson

Lesson

Pruning

A short lesson on pruning from the Model Adaptation & Inference Optimization micro course: what it is, where it shows up in real systems, and a practical example you can apply.

Open lesson

Lesson

Batching

A short lesson on batching from the Model Adaptation & Inference Optimization micro course: what it is, where it shows up in real systems, and a practical example you can apply.

Open lesson

Lesson

KV caching

A short lesson on KV caching from the Model Adaptation & Inference Optimization micro course: what it is, where it shows up in real systems, and a practical example you can apply.

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Lesson

Speculative decoding

A short lesson on speculative decoding from the Model Adaptation & Inference Optimization micro course: what it is, where it shows up in real systems, and a practical example you can apply.

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Model Adaptation & Inference Optimization

Recorded video

Start with the topic guide.

Concept scope

Prepare a focused example

Check your understanding

Need a walkthrough?Stay with this topic.

Request a live session for this topic.

Explore 13 focused topics.

Fine-tuning

Supervised fine-tuning

Parameter-efficient fine-tuning

LoRA

Preference optimization

Reinforcement learning from feedback

Distillation

Quantization

Pruning

Batching

KV caching

Speculative decoding

Need a walkthrough?
Stay with this topic.