58 lines
2.9 KiB
Markdown
58 lines
2.9 KiB
Markdown
|
---
|
||
|
|
license: apache-2.0
|
||
|
|
library_name: transformers
|
||
|
|
pipeline_tag: text-generation
|
||
|
|
---
|
||
|
|
# Qwen3-0.6B-Base
|
||
|
|
|
||
|
|
## Qwen3 Highlights
|
||
|
|
|
||
|
|
Qwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models.
|
||
|
|
Building upon extensive advancements in training data, model architecture, and optimization techniques, Qwen3 delivers the following key improvements over the previously released Qwen2.5:
|
||
|
|
|
||
|
|
- **Expanded Higher-Quality Pre-training Corpus:** Qwen3 is pre-trained on 36 trillion tokens across 119 languages — tripling the language coverage of Qwen2.5 — with a much richer mix of high-quality data, including coding, STEM, reasoning, book, multilingual, and synthetic data.
|
||
|
|
- **Training Techniques and Model Architecture:** Qwen3 incorporates a series of training techiques and architectural refinements, including global-batch load balancing loss for MoE models and qk layernorm for all models, leading to improved stability and overall performance.
|
||
|
|
- **Three-stage Pre-training:** Stage 1 focuses on broad language modeling and general knowledge acquisition, Stage 2 improves reasoning skills like STEM, coding, and logical reasoning, and Stage 3 enhances long-context comprehension by extending training sequence lengths up to 32k tokens.
|
||
|
|
- **Scaling Law Guided Hyperparameter Tuning:** Through comprehensive scaling law studies across the three-stage pre-training pipeline, Qwen3 systematically tunes critical hyperparameters — such as learning rate scheduler and batch size — separately for dense and MoE models, resulting in better training dynamics and final performance across different model scales.
|
||
|
|
|
||
|
|
## Model Overview
|
||
|
|
|
||
|
|
**Qwen3-0.6B-Base** has the following features:
|
||
|
|
- Type: Causal Language Models
|
||
|
|
- Training Stage: Pretraining
|
||
|
|
- Number of Parameters: 0.6B
|
||
|
|
- Number of Paramaters (Non-Embedding): 0.44B
|
||
|
|
- Number of Layers: 28
|
||
|
|
- Number of Attention Heads (GQA): 16 for Q and 8 for KV
|
||
|
|
- Context Length: 32,768
|
||
|
|
|
||
|
|
For more details, including benchmark evaluation, hardware requirements, and inference performance, please refer to our [blog](https://qwenlm.github.io/blog/qwen3/), [GitHub](https://github.com/QwenLM/Qwen3), and [Documentation](https://qwen.readthedocs.io/en/latest/).
|
||
|
|
|
||
|
|
## Requirements
|
||
|
|
|
||
|
|
The code of Qwen3 has been in the latest Hugging Face `transformers` and we advise you to use the latest version of `transformers`.
|
||
|
|
|
||
|
|
With `transformers<4.51.0`, you will encounter the following error:
|
||
|
|
```
|
||
|
|
KeyError: 'qwen3'
|
||
|
|
```
|
||
|
|
|
||
|
|
## Evaluation & Performance
|
||
|
|
|
||
|
|
Detailed evaluation results are reported in this [📑 blog](https://qwenlm.github.io/blog/qwen3/).
|
||
|
|
|
||
|
|
### Citation
|
||
|
|
|
||
|
|
If you find our work helpful, feel free to give us a cite.
|
||
|
|
|
||
|
|
```
|
||
|
|
@misc{qwen3technicalreport,
|
||
|
|
title={Qwen3 Technical Report},
|
||
|
|
author={Qwen Team},
|
||
|
|
year={2025},
|
||
|
|
eprint={2505.09388},
|
||
|
|
archivePrefix={arXiv},
|
||
|
|
primaryClass={cs.CL},
|
||
|
|
url={https://arxiv.org/abs/2505.09388},
|
||
|
|
}
|
||
|
|
```
|