🖐 HTML TIPS AND TRICKS
👏1
🚀 A fantastic resource for everyone who wants to understand how Qwen3 models work: Qwen3 From Scratch
This is a detailed step-by-step guide to running and analyzing Qwen3 models — from 0.6B to 32B — from scratch, directly in PyTorch.
📌 What's inside:
— How to load the Qwen3‑0.6B model and pretrained weights
— Setting up the tokenizer and generating text
— Support for the reasoning version of the model
— Tricks to speed up inference: compilation, KV cache, batching
📊 The author also compares Qwen3 with Llama 3:
✔️ Model depth vs width
✔️ Performance on different hardware
✔️ How the 0.6B, 1.7B, 4B, 8B, 32B models behave
⚡️ Perfect if you want to understand how inference, tokenization, and the Qwen3 architecture work — without magic or black boxes.
🖥 Github
This is a detailed step-by-step guide to running and analyzing Qwen3 models — from 0.6B to 32B — from scratch, directly in PyTorch.
📌 What's inside:
— How to load the Qwen3‑0.6B model and pretrained weights
— Setting up the tokenizer and generating text
— Support for the reasoning version of the model
— Tricks to speed up inference: compilation, KV cache, batching
📊 The author also compares Qwen3 with Llama 3:
✔️ Model depth vs width
✔️ Performance on different hardware
✔️ How the 0.6B, 1.7B, 4B, 8B, 32B models behave
⚡️ Perfect if you want to understand how inference, tokenization, and the Qwen3 architecture work — without magic or black boxes.
🖥 Github
🔥1