2026.06.07
Accessing and Selecting Gemma 4 QAT Checkpoints for Your Project
Learn how to access, understand, and select the right Gemma 4 Quantization-Aware Training (QAT) checkpoints for your mobile and laptop AI projects, …
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2026.06.07
Setting Up Your Development Environment and Running Initial Inference
Prepare your development environment, install necessary tools, and run your first inference with Google's Gemma 4 QAT models for optimized edge …
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Chapter 8: Syncing Local Experiments to Hugging Face Spaces
Learn how to sync local machine learning experiments with Hugging Face Spaces for remote collaboration and accessibility.
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Chapter 10: Fine-Tuning Large Language Models (LLMs)
Learn how to fine-tune Large Language Models for specific tasks using efficient techniques like PEFT and the Hugging Face library.
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Chapter 23: Project: Fine-Tuning an LLM for a Specific Task
Learn how to fine-tune a Large Language Model for a specific task using Parameter-Efficient Fine-Tuning techniques like LoRA.
ACCESS_FILE >>2026.05.19
Run MTP LLMs with llama.cpp & vLLM
Step-by-step tutorial: Run MTP LLMs with llama.cpp & vLLM. By the end of this tutorial, you will be able to set up and run Multi-Token Prediction …
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Trackio Practical Field Guide
A comprehensive guide to mastering Trackio, a lightweight tool for efficient machine learning experiment tracking.
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Learn Transformers.js: Revolutionizing AI in the Browser
Learn how to use Transformers.js to integrate powerful AI capabilities into web applications directly in the browser.
ACCESS_FILE >>2025.08.22
Mastering LLM Fine-tuning: Pre-training, SFT, and PEFT for Custom Models
A comprehensive guide to Large Language Model (LLM) pre-training and fine-tuning concepts, covering Supervised Fine-tuning (SFT), Parameter-Efficient …
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