← On-Device LLMs Hands-On: Prepare and Compress

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Section 3 · Lecture 2 · 9:12

kv cache and tokenizer efficiency

← slm definition and lineup language benchmarks and selection framework →

Curriculum

0/19 done

0. Welcome

welcome and course overview1m

1. On-Device AI and Mobile Hardware

Materials for this section

1 notebook

01_ondevice_ai_intro.ipynb

2. Model Compression Theory

Materials for this section

1 notebook

02_model_compression_theory.ipynb

3. Small Language Models

Materials for this section

1 notebook

03_slm_overview.ipynb

4. llama.cpp and GGUF

Materials for this section

1 notebook

04_llama_cpp_gguf_quantization.ipynb

5. MLC LLM

Materials for this section

1 notebook

05_mlc_llm_compilation.ipynb

6. ONNX Runtime Conversion

Materials for this section

1 notebook

06_onnx_llm_conversion.ipynb

Course-wide files

Applies to every section

1 doc

Notebook errata — licence warnings

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kv cache and tokenizer efficiency — On-Device LLMs Hands-On: Prepare and Compress | SOTAAZ Blog