The following steps are required to use Qwen3-8B-BitNet:
- environmental preparation: Install Python 3.8+ and create a virtual environment (recommended)
- Dependent Installation: Install the transformers and torch libraries via pip (GPU users need to install the CUDA version of PyTorch)
- Model loading: Loading models from Hugging Face using AutoModelForCausalLM and AutoTokenizer
Typical usage code example:
from transformers import AutoModelForCausalLM, AutoTokenizer
model_name = "codys12/Qwen3-8B-BitNet"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name,
torch_dtype="auto",
device_map="auto")
When generating text, you can toggle the thinking mode by setting the enable_thinking parameter with the apply_chat_template method.
This answer comes from the articleQwen3-8B-BitNet: an open source language model for efficient compressionThe
May not be reproduced without permission:AI productivity tools " How to install and use Qwen3-8B-BitNet for text generation?
English 
简体中文 
日本語 
Deutsch 
Português do Brasil